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Машинное обучение (Machine Learning)

Требуется помощь в преобразовании раздела Информатика и вычислительная техника

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2018. — 75 p. — ASIN B07FKZN93N. How can a beginner approach machine learning with Python from scratch? Why exactly is machine learning such a hot topic right now in the business world? Ahmed Ph. Abbasi will lead you from being a complete beginner in learning a sound method of data analysis that uses algorithms, which learn from data and produce actionable and valuable...
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2018. — 75 p. — ASIN B07FKZN93N. How can a beginner approach machine learning with Python from scratch? Why exactly is machine learning such a hot topic right now in the business world? Ahmed Ph. Abbasi will lead you from being a complete beginner in learning a sound method of data analysis that uses algorithms, which learn from data and produce actionable and valuable...
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2018.-75p.- ISBN-10 B07FKZN93N Machine Learning algorithms for beginners - data management and analytics for approaching deep learning and neural networks from scratch How can a beginner approach machine learning with Python from scratch? Why exactly is machine learning such a hot topic right now in the business world? Ahmed Ph. Abbasi will lead you from being a complete beginner...
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AI Sciences LLC, 2018. — 132 р. — ASIN B07GMVP3WP. Are you thinking of learning more about Machine Learning using Python? (For Beginners) This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the...
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AI Sciences LLC, 2018. — 132 р. — ASIN B07GMVP3WP. Are you thinking of learning more about Machine Learning using Python? (For Beginners) This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the...
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AI Sciences LLC, 2018. — 132 р. — ASIN B07GMVP3WP. Are you thinking of learning more about Machine Learning using Python? (For Beginners) This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the...
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Mercury Learning & Information, 2018. — 268 р. — ISBN 978-1683921325. This book, using an easy-to-follow, question and answer format provides readers with a brief introduction to the methods used in machine design. With over 1000 questions and answers on a variety of topics, it is an ideal resource for exam prep and for reviewing all of the key concepts in machine methods....
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Springer, 2018. — 493 p. — ISBN 978-3319735306. ext analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories: - Basic algorithms: Chapters 1...
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Springer, 2018. — 493 p. — ISBN 978-3319735306. Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories: - Basic algorithms: Chapters 1...
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Springer, 2018. — 512 p. — ISBN 3319944622. This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between...
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Springer, 2018. — 493 p. — ASIN B07BKQ1K1F. Artificial Intelligence, Data Mining Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories: -...
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2nd Edition. — MIT Press, 2010. — 581 p. Machine learning is programming computers to optimize a performance criterion using example data or past experience. We need learning in cases where we cannot directly write a computer program to solve a given problem, but need example data or experience. One case where learning is necessary is when human expertise does not exist, or when...
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3rd ed. — MIT Press, 2014. — 640 p. — ISBN 0262028182, 9780262028189 The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed...
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MIT Press, 2017. — 225 p. — (MIT Press essential knowledge). — ISBN 9780262529518. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition -- as well as some we dont yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data the...
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MIT, 2016. — 206 p. — ISBN 9780262529518 Alpaydın Ethem Machine Learning: The New AI Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition -- as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data;...
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Independently published, 2019. — 272 р. — ISBN 978-1793223012. New 2019 Edition! Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application. Deep Learning is the latest iteration of AI. Although the concept itself has...
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O'Reilly, 2020. — 303 p. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the tools, best practices, and...
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O'Reilly, 2020. — 150 p. — ISBN 978-1-492-04510-6. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the...
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O'Reilly, 2020. — 150 p. — ISBN 978-1-492-04510-6. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the...
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O'Reilly, 2020. — 150 p. — ISBN 978-1-492-04510-6. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the...
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O'Reilly, 2020. — 260 p. — ISBN 978-1-492-04510-6. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the...
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O'Reilly, 2020. — 260 p. — ISBN 978-1-492-04510-6. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the...
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O'Reilly, 2020. — 260 p. — ISBN 978-1-492-04510-6. Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the...
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Apress, 2018. - 510p. - ISBN: 978-1484238721 Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an...
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Apress, 2018. - 510p. - ISBN: 978-1484238721 Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an...
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New York: Springer, 2019. — 433 p. This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. After an introduction to the fundamentals, the book discusses in depth anomaly detection, data partitioning and clustering, as...
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Dordrecht: Springer Science+Business Media B.V, 2011. — 607 p. — ISBN 978-90-481-9419-3. A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October 20-22, 2009, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2009). Machine Learning and Systems Engineering contains...
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Cham: Springer International Publishing, 2018. — 118 p. — ISBN 978-3-319-71489-9. This book explores break-through approaches to tackling and mitigating the well-known problems of compiler optimization using design space exploration and machine learning techniques. It demonstrates that not all the optimization passes are suitable for use within an optimization sequence and that,...
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Springer, 2019. — 418 p. — ISBN 3030261522. The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks ) dealing not only with images and the use of computers, but also their applications to...
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Apress, 2018. - 362p. - ISBN: 1484235630 Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a...
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Apress, 2018. - 362p. - ISBN: 1484235630 Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a...
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Apress, 2018. — 362 p. — ISBN 1484235630. Code files only! Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so...
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Apress, 2018. — 362 p. — ISBN-13 (electronic): 978-1-4842-3564-5. Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in...
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Apress, 2018. — 362 p. — ISBN-13 (electronic): 978-1-4842-3564-5. Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in...
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Apress, 2018. — 362 p. — ISBN-13: 978-1-4842-3563-8 . Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that...
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Cambridge University Press, 2014. — 672 p. — ISBN: 978-0521518147. Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods...
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Khaled Bayoudh, 2017. — 166 p. There are a growing number of people who are seeking to understand the main concepts of Machine/Deep Learning and what powers them up. And if you are of these people, then this book is for you! This book discusses the Machine/Deep Learning algorithms, methods, concepts, functions and code that make Deep Neural Networks such as Convolutional Neural...
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Khaled Bayoudh, 2017. — 166 p. There are a growing number of people who are seeking to understand the main concepts of Machine/Deep Learning and what powers them up. And if you are of these people, then this book is for you! This book discusses the Machine/Deep Learning algorithms, methods, concepts, functions and code that make Deep Neural Networks such as Convolutional Neural...
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Cambridge University Press, 2011, 492 pages, 144 b/w illus. ISBN:9780521192248. This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset...
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Wiley, 2014. — 408 p. — ISBN: 1118889061 Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML...
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Wiley, 2014. — 408 p. — ISBN 1118889061. Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML...
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Wiley, 2014. — 408 p. — ISBN 1118889061. Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML...
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Springer, 2018 - 257 p. Machine learning of software artefacts is an emerging area of interaction between the machine learning and software analysis communities. Increased productivity in software engineering relies on the creation of new adaptive, scalable tools that can analyse large and continuously changing software systems. These require new software analysis techniques based...
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Springer, 2018 - 257 p. Machine learning of software artefacts is an emerging area of interaction between the machine learning and software analysis communities. Increased productivity in software engineering relies on the creation of new adaptive, scalable tools that can analyse large and continuously changing software systems. These require new software analysis techniques based...
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Packt Publishing, 2017. — 382 p. — ISBN 978-1-78398-028-4. Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. Machine Learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's...
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Apress, 2019. — 172 p. — ISBN 1484251261. Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym . Applied Reinforcement Learning with Python introduces you to the theory behind...
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2nd Edition. — Packt Publishing, 2018. — 300 p. — ISBN 978-1788474399. Key Features Solve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET libraries Practical examples, tips, and tricks to help you understand applied machine learning in Java Book Description As...
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Apress, 20198. — 354 p. — ISBN 978-1484251201. Explore machine learning in Rust and learn about the intricacies of creating machine learning applications. This book begins by covering the important concepts of machine learning such as supervised, unsupervised, and reinforcement learning, and the basics of Rust. Further, you’ll dive into the more specific fields of machine...
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De Gruyter, 2018. — 183 p. — (Frontiers In Computational Intelligence). — ISBN 978-3110550320. This volume comprises six well-versed contributed chapters devoted to report the latest findings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is...
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Packt Publishing, 2019. — 168 p. — ISBN 978-1838550356, 1838550356. This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key Features Your handy guide to building...
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Birmingham: Packt Publishing, 2019. - 158 p. - ISBN 1838550356. Key Features Your handy guide to building machine learning workflows in Go for real-world scenarios. Build predictive models using the popular supervised and unsupervised machine learning techniques. Learn all about deployment strategies and take your ML application from prototype to production ready Book Description...
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Apress, 2019. — 702 p. — ISBN 1484244699. Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform....
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Apress, 2019. — 702 p. — ISBN-13 (electronic): 978-1-4842-4470-8. ake a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of...
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Independently published, 2019. — 369 p. — ISBN 978-1686500237, 1686500238. Your Guide to Getting Ahead with Python! Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too. Machine Learning came into prominence in the 1990s, when researchers...
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Independently published, 2019. — 369 p. — ISBN 978-1686500237, 1686500238. Your Guide to Getting Ahead with Python! Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too. Machine Learning came into prominence in the 1990s, when researchers...
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Independently published, 2019. — 369 p. — ISBN 978-1686500237, 1686500238. Your Guide to Getting Ahead with Python! Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too. Machine Learning came into prominence in the 1990s, when researchers...
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Independently published, 2019. — 369 p. — ISBN 978-1686500237, 1686500238. Your Guide to Getting Ahead with Python! Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too. Machine Learning came into prominence in the 1990s, when researchers...
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Independently published, 2019. — 369 p. — ISBN 978-1686500237, 1686500238. Your Guide to Getting Ahead with Python! Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too. Machine Learning came into prominence in the 1990s, when researchers...
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Independently published, 2019. — 369 p. — ISBN 978-1686500237, 1686500238. Your Guide to Getting Ahead with Python! Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too. Machine Learning came into prominence in the 1990s, when researchers...
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Morgan & Claypool Publishers, 2019. — 175 p. — (Synthesis Lectures on Data Management). — ISBN 10 1681734982, 13 978-1681734989. Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML...
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Packt Publishing, 2019. — 386 p. — ISBN 978-1789348279, 1789348277. Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to...
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2nd. ed. - Birmingham: Packt Publishing, 2018. - 513 p. - ISBN 1789347998. Key Features Explore statistics and complex mathematics for data-intensive applications. Discover new developments in EM algorithm, PCA, and bayesian regression. Study patterns and make predictions across various datasets. Book Description Machine learning has gained tremendous popularity for its powerful...
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Packt Publishing, 2018. — 576 p. — ISBN 978-1788621113. Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their...
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Packt Publishing, 2018. — 576 p. — ISBN 978-1788621113. !Code files only Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and...
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Packt Publishing, 2018. — 576 p. — ISBN 978-1788621113. Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing machine learning algorithms and understand how they work in depth. One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their...
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Packt Publishing, 2019. — 375 p. — ISBN 978-1-78934-827-9. Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster...
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Packt Publishing, 2019. — 375 p. — ISBN 978-1-78934-827-9. Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster...
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Packt Publishing, 2019. — 426 p. — ISBN 978-1-78934-827-9. Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster...
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Packt Publishing, 2019. — 426 p. — ISBN 978-1-78934-827-9. Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster...
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Packt Publishing, 2019. — 375 p. — ISBN 978-1-78934-827-9. Code files only! Discover the skill-sets required to implement various approaches to Machine Learning with Python Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised...
  • №70
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Packt Publishing, 2017. — 449 p. — ISBN 978-1785889622. Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the...
  • №71
  • 8,14 МБ
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Packt Publishing, 2017. — 449 p. — ISBN 978-1785889622. Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide. About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the...
  • №72
  • 8,53 МБ
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Packt Publishing, 2017. — 449 p. — ISBN 978-1785889622. True PDF Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in...
  • №73
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2nd ed. — Packt Publishing, 2018. — 552 p. — ISBN 1789347998. An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Key Features Explore statistics and complex mathematics for data-intensive applications Discover new developments in EM algorithm, PCA, and bayesian regression Study patterns and make predictions...
  • №74
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2nd ed. — Packt Publishing, 2018. — 552 p. — ISBN 1789347998. An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Key Features Explore statistics and complex mathematics for data-intensive applications Discover new developments in EM algorithm, PCA, and bayesian regression Study patterns and make predictions...
  • №75
  • 87,83 МБ
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2nd Edition. — Packt Publishing, 2018. — 514 p. — ISBN 978-1-78934-799-9. Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Machine learning has gained tremendous popularity for its powerful and fast predictions...
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2nd Edition. — Packt Publishing, 2018. — 604 p. — ISBN 978-1-78934-799-9. Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Machine learning has gained tremendous popularity for its powerful and fast predictions...
  • №77
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2nd Edition. — Packt Publishing, 2018. — 604 p. — ISBN 978-1-78934-799-9. Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Machine learning has gained tremendous popularity for its powerful and fast predictions...
  • №78
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2nd Edition. — Packt Publishing, 2018. — 514 p. — ISBN 978-1-78934-799-9. Code files only! Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms Machine learning has gained tremendous popularity for its powerful and...
  • №79
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Packt Publishing, 2018. — 576 p. — ISBN 978-1-78862-111-3. Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models Explore and master the most important algorithms for solving complex machine learning problems. Machine learning is a subset of AI that aims to make modern-day computer systems smarter and...
  • №80
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Packt Publishing, 2018. — 646 p. — ISBN 978-1-78862-111-3. Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models Explore and master the most important algorithms for solving complex machine learning problems. Machine learning is a subset of AI that aims to make modern-day computer systems smarter and...
  • №81
  • 30,01 МБ
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Packt Publishing, 2018. — 646 p. — ISBN 978-1-78862-111-3. Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models Explore and master the most important algorithms for solving complex machine learning problems. Machine learning is a subset of AI that aims to make modern-day computer systems smarter and...
  • №82
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Packt Publishing, 2017. — 270 p. Your one-stop guide to becoming a Machine Learning expert. Most of us have heard about the term Machine Learning, but surprisingly the question frequently asked by developers across the globe is, “How do I get started in Machine Learning?”. One reason could be attributed to the vastness of the subject area because people often get overwhelmed by...
  • №83
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Bleeding Edge Press, 2018. — 243 p. This book covers the crossroads of web development and deep learning. Both technologies are beginning to meet, and this honeymoon will produce new fantastic applications that you cannot even imagine yet. In this book you will see how to use the main javascript deep learning frameworks and web programming in the browser with the capture of inputs...
  • №84
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Packt Publishing, 2015. — 190 p. — ISBN 978-1-78439-908-5. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences. Machine...
  • №85
  • 2,62 МБ
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Packt Publishing, 2015. — 190 p. — ISBN 978-1-78439-908-5. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences. Machine...
  • №86
  • 2,29 МБ
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Packt Publishing, 2015. — 190 p. — ISBN 978-1-78439-908-5. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences. Machine...
  • №87
  • 2,06 МБ
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Packt Publishing, 2015. — 190 p. — ISBN 978-1-78439-908-5. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences. Machine...
  • №88
  • 2,35 МБ
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Independently published, 2018. — 79 р. Do you want to impress the processes that you are working on? Do you want to make your machines more intelligent? If your answer to any of those questions is yes, then you have come to the right place. This book is a sequel to the book titled 'Machine Learning: A Step-by-Step guide.' In the first book, you gathered information on what machine...
  • №89
  • 4,80 МБ
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Independently published, 2018. — 79 р. Do you want to impress the processes that you are working on? Do you want to make your machines more intelligent? If your answer to any of those questions is yes, then you have come to the right place. This book is a sequel to the book titled 'Machine Learning: A Step-by-Step guide.' In the first book, you gathered information on what machine...
  • №90
  • 565,90 КБ
  • добавлен
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Independently published, 2018. — 79 р. Do you want to impress the processes that you are working on? Do you want to make your machines more intelligent? If your answer to any of those questions is yes, then you have come to the right place. This book is a sequel to the book titled 'Machine Learning: A Step-by-Step guide.' In the first book, you gathered information on what machine...
  • №91
  • 548,38 КБ
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New York: Jason Brownlee., 2018. — 212 p. Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this new laser-focused Ebook written in the friendly Machine Learning Mastery style that you’re used to, you will finally cut through the equations, Greek letters, and confusion, and discover the topics...
  • №92
  • 1,34 МБ
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Machine Learning Mastery, 2016. — 179 p. The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this mega Ebook written in the friendly Machine Learning Mastery style...
  • №93
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New York: Jason Brownlee., 2018. — 291 p. — ISBN N\A. The information contained within this eBook is strictly for educational purposes. If you wish to apply ideas contained in this eBook, you are taking full responsibility for your actions. The author has made every e_ort to ensure the accuracy of the information within this book was correct at time of publication. The author does...
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Edition 1.4. — 2018. — 574 p. Preface Introduction Foundations Promise of Deep Learning for Time Series Forecasting Time Series Forecasting Convolutional Neural Networks for Time Series Recurrent Neural Networks for Time Series Promise of Deep Learning Extensions Further Reading Summary Taxonomy of Time Series Forecasting Problems Framework Overview Inputs vs. Outputs Endogenous...
  • №95
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Machine Learning Mastery, 2018. — 115 р. Welcome to XGBoost With Python. This book is your guide to fast gradient boosting in Python. You will discover the XGBoost Python library for gradient boosting and how to use it to develop and evaluate gradient boosting models. In this book you will discover the techniques, recipes and skills with XGBoost that you can then bring to your own...
  • №96
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Machine Learning Mastery, 2018. — 115 р. Welcome to XGBoost With Python. This book is your guide to fast gradient boosting in Python. You will discover the XGBoost Python library for gradient boosting and how to use it to develop and evaluate gradient boosting models. In this book you will discover the techniques, recipes and skills with XGBoost that you can then bring to your own...
  • №97
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With contributions by Nicholas Locascio. — New York: O’Reilly Media, 2017. — 298 p. — ISBN: 978-1-491-92561-4. With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated...
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O'Reilly, 2018. - 226p. - ISBN: 1491976446 Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, youll first start to learn with regression modelling and then move into more advanced topics...
  • №99
  • 5,07 МБ
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O'Reilly, 2018. — 226 p. — ISBN 1491976446. Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, youll first start to learn with regression modelling and then move into more advanced topics...
  • №100
  • 3,81 МБ
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Б.м.и.: Andriy Burkov, 2019. — 152 p. Is this book for you? You will enjoy the book if you are: - a software engineer or a scientist who wants to become a machine learning engineer or a data scientist - a data scientist trying to stay on the edge of the state-of-the-art and deepen their ML expertise - a manager who wants to feel confident while talking about AI with engineers and...
  • №101
  • 6,98 МБ
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Globaltech NTC, 2018. — 144 р. You are interested in becoming a machine learning expert but don't know where to start from? Don't worry you don't need a big boring and expensive Textbook. This book is the best guide for you. Here are the reasons: The author has explored everything about machine learning and deep learning right from the basics. A simple language has been used.Many...
  • №102
  • 610,13 КБ
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Globaltech NTC, 2018. — 144 р. You are interested in becoming a machine learning expert but don't know where to start from? Don't worry you don't need a big boring and expensive Textbook. This book is the best guide for you. Here are the reasons: The author has explored everything about machine learning and deep learning right from the basics. A simple language has been used.Many...
  • №103
  • 6,18 МБ
  • добавлен
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Globaltech NTC, 2018. — 144 р. You are interested in becoming a machine learning expert but don't know where to start from? Don't worry you don't need a big boring and expensive Textbook. This book is the best guide for you. Here are the reasons: The author has explored everything about machine learning and deep learning right from the basics. A simple language has been used.Many...
  • №104
  • 1,89 МБ
  • добавлен
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Globaltech NTC, 2018. — 144 р. You are interested in becoming a machine learning expert but don't know where to start from? Don't worry you don't need a big boring and expensive Textbook. This book is the best guide for you. Here are the reasons: The author has explored everything about machine learning and deep learning right from the basics. A simple language has been used.Many...
  • №105
  • 655,18 КБ
  • добавлен
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2nd edition. — Morgan & Claypool, 2018. — 207 p. — ISBN 978-1681733043. Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a...
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  • 2,07 МБ
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2nd edition. — Morgan & Claypool, 2018. — 207 p. — ISBN 978-1681733043. Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a...
  • №107
  • 2,69 МБ
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New York: Morgan & Claypool, 2017. — 128 p. Lifelong Machine Learning (or Lifelong Learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the...
  • №108
  • 754,09 КБ
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Packt Publishing, 2018. — 500 p. — ISBN 1509304444. Unleash Google's Cloud Platform to build, train and optimize machine learning models Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at...
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Packt Publishing, 2018. — 500 p. — ISBN 1509304444. !Only code files Unleash Google's Cloud Platform to build, train and optimize machine learning models Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine...
  • №110
  • 1,85 МБ
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Packt Publishing, 2018. — 500 p. — ISBN 1509304444. Unleash Google's Cloud Platform to build, train and optimize machine learning models Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at...
  • №111
  • 26,49 МБ
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Packt, 2018. — 406 p. — ISBN 978-1788623223. Develop your own Python-based machine learning system. Discover how Python offers multiple al Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This...
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Packt Publishing, 2016. — 324 p. — ISBN 1784394750, 9781784394752. Machine Learning is transforming the way we understand and interact with the world around us. But how much do you really understand it? How confident are you interacting with the tools and models that drive it? Python Machine Learning Blueprints puts your skills and knowledge to the test, guiding you through the...
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2nd Edition. — Packt Publishing, 2019. — 378 р. — ISBN 978-1788994170. Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the...
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2nd Edition. — Packt Publishing, 2019. — 372 p. — ISBN 978-1-78899-417-0. Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to...
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2nd Edition. — Packt Publishing, 2019. — 371 p. — ISBN 978-1-78899-417-0. Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to...
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2nd Edition. — Packt Publishing, 2019. — 433 p. — ISBN 978-1-78899-417-0. Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to...
  • №117
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2nd Edition. — Packt Publishing, 2019. — 433 p. — ISBN 978-1-78899-417-0. Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to...
  • №118
  • 35,10 МБ
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2nd Edition. — Packt Publishing, 2019. — 433 p. — ISBN 978-1-78899-417-0. Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to...
  • №119
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2nd Edition. — Packt Publishing, 2019. — 372 p. — ISBN 978-1-78899-417-0. Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to...
  • №120
  • 51,27 МБ
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O'Reilly Media, 2016. — 300 p. — ISBN 10 149196460X, ISBN 13 978-1491964606. Machine learning has finally come of age. With H 2 O software, you can perform machine learning and data analysis using a simple open source framework that's easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H 2 0 with only...
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Издательство Springer, 2008, -296 pp. Large collections of digital multimedia data are continuously created in different fields and in many application contexts. Application domains include web searching, cultural heritage, geographic information systems, biomedicine, surveillance systems, etc. The quantity, complexity, diversity and multi-modality of these data are all...
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Packt Publishing, 2017. — 450 p. — ISBN 978-1-78829-575-8. True PDF Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain...
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Packt Publishing, 2017. — 442 p. — ISBN 9781788295758. Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on...
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  • 12,03 МБ
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Packt Publishing, 2017. — 438 p. — ISBN 978-1788294041. An effective guide to using ensemble techniques to enhance machine learning models Key Features Learn how to maximize popular machine learning algorithms such as random forests, decision trees, AdaBoost, K-nearest neighbor, and more Get a practical approach to building efficient machine learning models using ensemble...
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  • 15,18 МБ
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Packt Publishing, 2017. — 438 p. — ISBN 978-1788294041. An effective guide to using ensemble techniques to enhance machine learning models. Key Features Learn how to maximize popular machine learning algorithms such as random forests, decision trees, AdaBoost, K-nearest neighbor, and more Get a practical approach to building efficient machine learning models using ensemble...
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Packt Publishing, 2017. — 438p. — ISBN 978-1788294041. !Code files only An effective guide to using ensemble techniques to enhance machine learning models Key Features Learn how to maximize popular machine learning algorithms such as random forests, decision trees, AdaBoost, K-nearest neighbor, and more Get a practical approach to building efficient machine learning models using...
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  • 6,15 МБ
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Packt, 2016. — 358 p. — ISBN 978-1-78588-840-3. Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0 Set up your business application to start using machine learning techniques Familiarize the user with some of the more common .NET libraries for machine learning Implement several common machine learning techniques Evaluate, optimize and adjust machine learning...
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2nd. ed. — Springer-Verlag London, 2019. — 995 p. — ISBN 1447174518. This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows...
  • №129
  • 22,67 МБ
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Pearson, 2018. — 456 p. — ISBN 9353066697. Readers of this book will gain a thorough understanding of machine learning concepts. Not only students but also software professionals will find a variety of techniques with sufficient discussions in this book that cater to the needs of the professional environments. Technical managers will get an insight into weaving machine learning...
  • №130
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Apress, 2019. - 365p. - ISBN: 9781484236574 Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. The ability to analyze massive amounts of real-time data and predict future behavior of...
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  • 28,61 МБ
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Apress, 2019. - 365p. - ISBN: 9781484236574 Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. The ability to analyze massive amounts of real-time data and predict future behavior of...
  • №132
  • 29,54 МБ
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New York: Chapman and Hall/CRC, 2019. — 335 c. Machine Learning is known under many names such as Machine Learning, Artificial Intelligence, Pattern Recognition, Data Mining, Data Assimilation, and Big Data, to list but a few. It developed in many areas of science, such as in physics, engineering, computer science, and mathematics in parallel and independently. For example it is...
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  • 21,10 МБ
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New York: Addison-Wesley Professional, 2019. — 592 p. The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyonewill help you master the processes, patterns, and strategies you need to build effective learning systems, even if you're an absolute beginner. If you can write some Python code, this book is...
  • №134
  • 15,52 МБ
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Addison-Wesley Professional, 2019. — 592 р. — (Addison-Wesley Data & Analytics Series). — ISBN 978-0134845623. Полное руководство для начинающих по изучению и созданию систем машинного обучения с использованием Python. Книга "Машинное обучение с Python для всех" поможет вам освоить процессы, шаблоны и стратегии, необходимые для построения эффективных систем обучения, даже если вы...
  • №135
  • 14,87 МБ
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Addison-Wesley Professional, 2019. — 592 р. — (Addison-Wesley Data & Analytics Series). — ISBN 978-0134845623. Полное руководство для начинающих по изучению и созданию систем машинного обучения с использованием Python. Книга "Машинное обучение с Python для всех" поможет вам освоить процессы, шаблоны и стратегии, необходимые для построения эффективных систем обучения, даже если вы...
  • №136
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Addison-Wesley Professional, 2019. — 592 р. — (Addison-Wesley Data & Analytics Series). — ISBN 978-0134845623. The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyonewill help you master the processes, patterns, and strategies you need to build effective learning systems, even if you're an absolute...
  • №137
  • 39,89 МБ
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Выходные данные не указаны. — 291 p. Edited by Tomasz Pawlak to match requirements of course of Applications of Computational Intelligence Methods at Poznan University of Technology, Faculty of Computing. As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles....
  • №138
  • 4,93 МБ
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Выходные данные не указаны. — 291 p. Edited by Tomasz Pawlak to match requirements of course of Applications of Computational Intelligence Methods at Poznan University of Technology, Faculty of Computing. As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles....
  • №139
  • 3,20 МБ
  • добавлен
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Cambridge University Press, 2012. — 396 p. — ISBN: 978-1107096394. As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine...
  • №140
  • 4,90 МБ
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Springer, 2019. — 494 p. — ISBN 3030181138, 9783030181130. Machine learning methods are now an important tool for scientists, researchers, engineers and students in a wide range of areas. This book is written for people who want to adopt and use the main tools of machine learning, but aren’t necessarily going to want to be machine learning researchers. Intended for students in...
  • №141
  • 9,34 МБ
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USA: Applied Data Science Partners Ltd, 2019. — 330 p. — ISBN 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
  • №142
  • 39,17 МБ
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O'Reilly Media, 2019. — 55 р. — ISBN 1492041947. Generative modeling is one of the hottest topics in artificial intelligence (AI). Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors—such as drawing, composing music, and completing tasks—by generating an understanding of how its actions affect its environment. With this...
  • №143
  • 10,45 МБ
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O'Reilly Media, 2019. — 55 р. — ISBN 1492041947. Generative modeling is one of the hottest topics in artificial intelligence (AI). Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors—such as drawing, composing music, and completing tasks—by generating an understanding of how its actions affect its environment. With this...
  • №144
  • 1,57 МБ
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Applied Data Science Partners Ltd, 2019. — 330 p. — ISBN 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
  • №145
  • 6,71 МБ
  • добавлен
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Applied Data Science Partners Ltd, 2019. — 330 p. — ISBN 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
  • №146
  • 29,19 МБ
  • добавлен
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Applied Data Science Partners Ltd, 2019. — 308 p. — ISBN 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
  • №147
  • 19,50 МБ
  • добавлен
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Applied Data Science Partners Ltd, 2019. — 308 p. — ISBN 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
  • №148
  • 38,83 МБ
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Chapman and Hall/CRC, 2017. — 300 p. — ISBN 978-1138197152. True PDF Excel Visual Basic for Applications (VBA) can be used to automate operations in Excel and is one of the most frequently used software programs for manipulating data and building models in banks and insurance companies. An Introduction to Excel VBA Programming: with Applications in Finance and Insurance introduces...
  • №149
  • 31,03 МБ
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Amazon Digital Services LLC, 2018. — 770 р. The last decade and some, has witnessed some remarkable advancements in the area of Deep Learning. This area of Artificial intelligence (AI) has proliferated into many branches - Deep Belief Networks, Recurrent Neural Networks, Convolution Neural Networks, Adversorial Networks, Reinforcement Learning, Capsule Networks and the list goes...
  • №150
  • 8,48 МБ
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2nd Edition. — Amazon Digital Services LLC, 2018. — 770 р. The last decade and some, has witnessed some remarkable advancements in the area of Deep Learning. This area of Artificial intelligence (AI) has proliferated into many branches - Deep Belief Networks, Recurrent Neural Networks, Convolution Neural Networks, Adversorial Networks, Reinforcement Learning, Capsule Networks and...
  • №151
  • 3,71 МБ
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Third Edition. — 2018. — 442 p. This book implements many common Machine Learning algorithms in equivalent R and Python. This is the 3rd edition of the book. The book touches on R and Python implementations of different regression models, classification algorithms including logistic regression, KNN classification, SVMs, b-splines, random forest, boosting etc. Other techniques like...
  • №152
  • 7,53 МБ
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Монография 2018. - 442 с. На английском языке. Эта книга реализует много общих алгоритмов машинного обучения в эквивалентных R и Python. Это 3-е издание книги. В книге рассматриваются реализации R и Python различных регрессионных моделей, алгоритмы классификации, в том числе логистическая регрессия, классификация KNN, SVM, b-сплайны, случайный лес, форсирование и т. д. Далее в...
  • №153
  • 2,97 МБ
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O'Reilly Media, 2018. — 526 p. — ISBN 978-1492044819, 1492044814. Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you’ll learn how to build features that use powerful AI...
  • №154
  • 38,14 МБ
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O'Reilly, 2017. — 581 p. — ISBN 9781491962299. Only sample files ! Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete...
  • №155
  • 13,22 МБ
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O'Reilly, 2017. — 1139 p. — ISBN 978-1-491-96229-9. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal...
  • №156
  • 20,04 МБ
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Second updated edition. — O'Reilly, 2019. — 856 p. — ISBN 1492032646. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete...
  • №157
  • 46,63 МБ
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Early Release. — 2nd edition. — O'Reilly, 2019. — 510 p. — ISBN 978-1-492-03264-9. Concepts, Tools, and Techniques to Build Intelligent Systems Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable...
  • №158
  • 19,60 МБ
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2nd edition. — O’Reilly Media, Inc., 2019. — 519 p. — ISBN 978-1-492-03264-9. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling...
  • №159
  • 46,17 МБ
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2nd edition. — O’Reilly Media, Inc., 2019. — 519 p. — ISBN 978-1-492-03264-9. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling...
  • №160
  • 17,42 МБ
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2nd edition. — O’Reilly Media, Inc., 2019. — 519 p. — ISBN 978-1-492-03264-9. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling...
  • №161
  • 35,49 МБ
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Early Release. 2nd Edition. — O'Reilly, 2019. — 600 р. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling book uses concrete...
  • №162
  • 31,52 МБ
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Early Release . 2nd Edition. — O'Reilly, 2019. — 600 р. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling book uses concrete...
  • №163
  • 35,41 МБ
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2nd Edition. (3rd. Rev.) — O'Reilly, 2019. — 856 р. - ISBN: 1492032646 Final Edition Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this...
  • №164
  • 46,80 МБ
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2nd Edition. — O'Reilly, 2019. — 856 р. - ISBN: 1492032646 Final Edition Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling book...
  • №165
  • 54,00 МБ
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2nd Edition. — O’Reilly Media, Inc., 2019. — 856 p. - ISBN: 978-1-492-03264-9. Final Edition Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you...
  • №166
  • 13,43 МБ
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Second updated edition. — O’Reilly Media, Inc., 2019. — 901 p. - ISBN: 978-1-492-03264-9. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you...
  • №167
  • 31,66 МБ
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Second updated edition. — O’Reilly Media, Inc., 2019. — 901 p. - ISBN: 978-1-492-03264-9. Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you...
  • №168
  • 46,72 МБ
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Addison-Wesley Professional, 2018. — 611 p. — ISBN 13: 978-0-13-486386-3. Искусственный интеллект - это мощный инструмент в руках современного архитектора, разработчика и аналитика. Облачные технологии - ваш путь к укрощению искусственного интеллекта. Тщательно изучив эту незаменимую книгу от Ноя Гифта, легендарного эксперта по языку Python, вы легко научитесь писать облачные...
  • №169
  • 18,94 МБ
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Addison-Wesley Professional, 2018. — 611 p. — ISBN 13: 978-0-13-486386-3. Искусственный интеллект - это мощный инструмент в руках современного архитектора, разработчика и аналитика. Облачные технологии - ваш путь к укрощению искусственного интеллекта. Тщательно изучив эту незаменимую книгу от Ноя Гифта, легендарного эксперта по языку Python, вы легко научитесь писать облачные...
  • №170
  • 19,03 МБ
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O'Reilly Media, 2018. — 45 p. — ISBN 9781492033158. Innovation and competition are driving analysts and data scientists toward increasingly complex predictive modeling and machine learning algorithms. This complexity makes these models accurate but also makes their predictions difficult to understand. When accuracy outpaces interpretability, human trust suffers, affecting business...
  • №171
  • 4,81 МБ
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O'Reilly Media, 2018. — 45 p. — ISBN 9781492033158. Innovation and competition are driving analysts and data scientists toward increasingly complex predictive modeling and machine learning algorithms. This complexity makes these models accurate but also makes their predictions difficult to understand. When accuracy outpaces interpretability, human trust suffers, affecting business...
  • №172
  • 697,43 КБ
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Amazon Digital Services, 2018. — 1750 p. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The book takes a...
  • №173
  • 130,28 МБ
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Digital Services LLC, 2018. — 910 p. — ASIN B079XSQNRX. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The book...
  • №174
  • 22,42 МБ
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Digital Services LLC, 2018. — 914 p. — ASIN: B079Y1M81K. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The book...
  • №175
  • 24,79 МБ
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Amazon Digital Services, 2018. — 1750 p. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The book takes a...
  • №176
  • 143,63 МБ
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Packt Publishing, 2016. — 625 p. — ISBN-10: 178439968X. — ISBN-13: 978-1784399689 This book has been created for data scientists who want to see Machine learning in action and explore its real-world applications. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. About This Book Fully-coded working examples using a...
  • №177
  • 17,79 МБ
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Packt Publishing - ebooks Account, 2016. — 614 p. — ISBN-10: 178439968X. — ISBN-13: 978-1784399689 This book has been created for data scientists who want to see Machine learning in action and explore its real-world applications. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. About This Book Fully-coded working...
  • №178
  • 17,93 МБ
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Packt Publishing, 2016. — 653 p. — ISBN-10: 178439968X. — ISBN-13: 978-1784399689 This book has been created for data scientists who want to see Machine learning in action and explore its real-world applications. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. About This Book Fully-coded working examples using a...
  • №179
  • 16,56 МБ
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Packt Publishing, 2016. — 614 p. — ISBN-10 178439968X. — ISBN-13 978-1784399689. This book has been created for data scientists who want to see Machine learning in action and explore its real-world applications. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately. About This Book Fully-coded working examples using a wide...
  • №180
  • 18,79 МБ
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McGraw-Hill Education, 2019. — 656 p. — ISBN 978-1260456844, 1260456846. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical under¬pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning...
  • №181
  • 12,76 МБ
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McGraw-Hill Education, 2019. — 656 p. — ISBN 978-1260456844, 1260456846. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical under¬pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning...
  • №182
  • 12,82 МБ
  • добавлен
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McGraw-Hill Education, 2019. — 656 p. — ISBN 978-1260456844, 1260456846. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical under¬pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning...
  • №183
  • 4,04 МБ
  • добавлен
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McGraw-Hill Education, 2019. — 656 p. — ISBN 978-1260456844, 1260456846. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical underpinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning...
  • №184
  • 16,23 МБ
  • добавлен
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McGraw-Hill Education, 2019. — 656 p. — ISBN 978-1260456844, 1260456846. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical under¬pinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning...
  • №185
  • 10,70 МБ
  • добавлен
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Birmingham: Packt Publishing, 2018. — 263 p. — ISBN 1788629353. Leverage the power of machine learning on mobiles and build intelligent mobile applications with ease ! Key Features Build smart mobile applications for Android and iOS devices. Use popular machine learning toolkits such as Core ML and TensorFlow Lite. Explore cloud services for machine learning that can be used in...
  • №186
  • 11,24 МБ
  • добавлен
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Addison-Wesley Professional, 2019. — 655 p. — (Addison-Wesley Data & Analytics Series). — ISBN 013517238. Rough Cuts (Work in Progress) ! The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice. Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential...
  • №187
  • 13,39 МБ
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Addison-Wesley Professional, 2020. — 817 p. — Addison-Wesley Professional, 2019. — 655 p. — Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such...
  • №188
  • 22,73 МБ
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Addison-Wesley Professional, 2019. — 416 p. — ISBN: 978-0135172384. The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable...
  • №189
  • 21,79 МБ
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Addison-Wesley Professional, 2019. — 416 p. — ISBN: 978-0135172384. The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable...
  • №190
  • 22,20 МБ
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New York: Springer, 2019. — 372 p. This book presents ground-breaking advances in the domain of causal structure learning. The problem of distinguishing cause from effect (“Does altitude cause a change in atmospheric pressure, or vice versa?”) is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of the ChaLearn...
  • №191
  • 9,10 МБ
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Birmingham: Packt Publishing, 2019. — 199 p. — ISBN 1789345804. Key Features Use Q-learning to train deep learning models using Markov decision processes (MDPs). Study practical deep reinforcement learning using deep Q-networks. Explore state-based unsupervised learning for machine learning models. Book Description Q-learning is a machine learning algorithm used to solve...
  • №192
  • 9,48 МБ
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Birmingham: Packt Publishing, 2019. — 199 p. — ISBN 1789345804. Python code files for the book ! Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping...
  • №193
  • 183,07 КБ
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Packt Publishing, 2019. — 199 p. — ISBN 978-1-78934-580-3. Leverage the power of reward-based training for your deep learning models with Python Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement...
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  • 2,63 МБ
  • добавлен
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Packt Publishing, 2019. — 295 p. — ISBN 978-1-78934-580-3. Leverage the power of reward-based training for your deep learning models with Python Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement...
  • №195
  • 16,62 МБ
  • добавлен
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Packt Publishing, 2019. — 295 p. — ISBN 978-1-78934-580-3. Leverage the power of reward-based training for your deep learning models with Python Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement...
  • №196
  • 9,63 МБ
  • добавлен
  • изменен
Packt Publishing, 2019. — 295 p. — ISBN 978-1-78934-580-3. Leverage the power of reward-based training for your deep learning models with Python Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement...
  • №197
  • 9,58 МБ
  • добавлен
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Independently published, 2019. - 435 p. - ISBN 1710263423. Created with the beginner in mind , this powerful bundle delves into the fundamentals behind Python and Machine Learning , from basic code and mathematical formulas to complex neural networks and ensemble modeling. Inside, you’ll discover everything you need to know to get started with Python and Machine Learning, and...
  • №198
  • 4,95 МБ
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Birmingham: Packt Publishing, 2018. — 305 p. — ISBN 1788992288. Get into the world of smart data security using machine learning algorithms and Python libraries ! Key Features Learn machine learning algorithms and cybersecurity fundamentals. Automate your daily workflow by applying use cases to many facets of security. Implement smart machine learning solutions to detect various...
  • №199
  • 10,99 МБ
  • добавлен
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O'Reilly Media, 2020. — 168 p. — (Early Release). Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that...
  • №200
  • 7,17 МБ
  • добавлен
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O'Reilly Media, 2020. — 168 p. — (Early Release). Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that...
  • №201
  • 2,55 МБ
  • добавлен
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O'Reilly Media, 2020. — 168 p. — (Early Release). Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that...
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  • 1,28 МБ
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Apress, 2017. — 204 p. - ISBN: 978-1-4842-2823-4 Code files only! Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes...
  • №203
  • 9,72 МБ
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Apress, 2017. — 204 p. Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and...
  • №204
  • 3,75 МБ
  • добавлен
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Apress, 2017. — 204 p. Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and...
  • №205
  • 7,95 МБ
  • добавлен
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Manning Publications, 2012. — 384 p. — ISBN 1617290181, 9781617290183. Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting,...
  • №206
  • 8,51 МБ
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O'Reilly, 2019. — 320 p. — ISBN 1492047546. !Code files only With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal...
  • №207
  • 6,66 МБ
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O'Reilly, 2019. — 320 p. — ISBN 1492047546. With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers,...
  • №208
  • 23,32 МБ
  • добавлен
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Springer, 2018. — 472 p. — (Studies in Computational Intelligence 801). — ISBN 978-3-030-02356-0. The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world...
  • №209
  • 20,92 МБ
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Springer, 2018. — 472 p. — ISBN 978-3-030-02356-0. — (Studies in Computational Intelligence 801). The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world...
  • №210
  • 6,40 МБ
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London, United Kingdom: Institution of Engineering and Technology, 2019. — 350 p. — ISBN 978-1785616570, 1785616579. Machine learning explores the study and development of algorithms that can learn from and make predictions and decisions based on data. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big...
  • №211
  • 25,41 МБ
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IOS Press, 2017. — 284 p. Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from...
  • №212
  • 11,94 МБ
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2018. — 132 p. — ISBN 1727337964. Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Deep learning is a powerful data tool that can help improve businesses. In this book, you will learn: Neural networks Machine learning How it relates to certain...
  • №213
  • 660,03 КБ
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2018. — 132 p. — ISBN 1727337964. Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Deep learning is a powerful data tool that can help improve businesses. In this book, you will learn: Neural networks Machine learning How it relates to certain...
  • №214
  • 931,43 КБ
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2018. — 246 p. — ISBN 1727338944. Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Machine Learning and Deep learning are powerful data tools that can help improve businesses. In this book, you will learn: Neural networks Machine learning Python and...
  • №215
  • 1,03 МБ
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2018. — 246 p. — ISBN 1727338944. Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Machine Learning and Deep learning are powerful data tools that can help improve businesses. In this book, you will learn: Neural networks Machine learning Python and...
  • №216
  • 693,91 КБ
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Springer, 2020. — 157 p. — (Computer Architecture and Design Methodologies). — ISBN 978-981-13-3322-4. This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture...
  • №217
  • 8,94 МБ
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Cham: Springer International Publishing, 2019. — 168 p. — ISBN 978-3-030-06073-2. The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how...
  • №218
  • 4,43 МБ
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Manning, 2019. — 288 p. — ISBN 1617295833. !Code files Machine learning can deliver these and other advantages to your business, and it’s never been easier to get started! Machine Learning for Business teaches you how to make your company more automated, productive, and competitive by mastering practical, implementable machine learning techniques and tools. Thanks to the authors’...
  • №219
  • 29,53 МБ
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Springer, 2019. — 219 p. — ISBN 3030053172. This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of...
  • №220
  • 6,54 МБ
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Frank Hutter, Lars Kotthof, Joaquin Vanschoren. — Springer, 2019. — 219 p. — ISBN 978-3-030-05318-5. В этой книге представлен первый всеобъемлющий обзор общих методов автоматического машинного обучения (AutoML), собраны описания существующих систем на основе этих методов и обсуждена первая серия международных проблем систем AutoML. Недавний успех коммерческих приложений машинного...
  • №221
  • 13,17 МБ
  • добавлен
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Frank Hutter, Lars Kotthof, Joaquin Vanschoren. — Springer, 2019. — 219 p. — ISBN 978-3-030-05318-5. В этой книге представлен первый всеобъемлющий обзор общих методов автоматического машинного обучения (AutoML), собраны описания существующих систем на основе этих методов и обсуждена первая серия международных проблем систем AutoML. Недавний успех коммерческих приложений машинного...
  • №222
  • 7,58 МБ
  • добавлен
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Frank Hutter, Lars Kotthof, Joaquin Vanschoren. — Springer, 2019. — 219 p. — ISBN 978-3-030-05318-5. В этой книге представлен первый всеобъемлющий обзор общих методов автоматического машинного обучения (AutoML), собраны описания существующих систем на основе этих методов и обсуждена первая серия международных проблем систем AutoML. Недавний успех коммерческих приложений машинного...
  • №223
  • 13,35 МБ
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The MIT Press, 2017. — 624 p. — ISBN 026203641X. The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage,...
  • №224
  • 80,79 МБ
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The MIT Press, 2017. — 624 p. — ISBN 026203641X. The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies. This is the first textbook to teach students how to build data analytic solutions on large data sets (specifically in Internet of Things applications) using cloud-based technologies for data storage,...
  • №225
  • 63,77 МБ
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Packt Publishing, 2018. — 350 p. — ISBN 1788996402. Power up your C# and .NET applications with exciting machine learning models and modular projects Key Features Produce classification, regression, association and clustering models Expand your understanding of machine learning and C# Get the grips of C# packages such as Accord.net, LiveCharts, Deedle Book Description Machine...
  • №226
  • 5,46 МБ
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Packt Publishing, 2018. — 350 p. — ISBN 1788996402. Power up your C# and .NET applications with exciting machine learning models and modular projects Key Features Produce classification, regression, association and clustering models Expand your understanding of machine learning and C# Get the grips of C# packages such as Accord.net, LiveCharts, Deedle Book Description Machine...
  • №227
  • 12,54 МБ
  • добавлен
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Packt Publishing, 2018. — 254 р. — ISBN 978-1789806199. Use artificial intelligence and machine learning on AWS to create engaging applications Key Features Explore popular AI and ML services with their underlying algorithms Use the AWS environment to manage your AI workflow Reinforce key concepts with hands-on exercises using real-world datasets Book DescriptionMachine Learning...
  • №228
  • 7,54 МБ
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Packt Publishing, 2018. — 254 p. — ISBN 978-1789806199. Use artificial intelligence and machine learning on AWS to create engaging applications Key Features Explore popular AI and ML services with their underlying algorithms Use the AWS environment to manage your AI workflow Reinforce key concepts with hands-on exercises using real-world datasets Book DescriptionMachine Learning...
  • №229
  • 6,13 МБ
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Springer, 2011. — 370 p. Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition,...
  • №230
  • 4,66 МБ
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Packt Publishing, 2019. — 456 p. — ISBN 1789136364. A guide to advances in machine learning for financial professionals, with working Python code. Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms behind the...
  • №231
  • 23,61 МБ
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Packt Publishing, 2019. — 456 p. — ISBN 1789136364. A guide to advances in machine learning for financial professionals, with working Python code. Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms behind the...
  • №232
  • 14,85 МБ
  • добавлен
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Packt Publishing, 2019. — 456 p. — ISBN 1789136364. Code files only! A guide to advances in machine learning for financial professionals, with working Python code. Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and...
  • №233
  • 2,70 МБ
  • добавлен
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Packt Publishing, 2019. — 456 p. — ISBN 978-1-78913-636-4. A guide to advances in machine learning for financial professionals, with working Python code. Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms...
  • №234
  • 20,05 МБ
  • добавлен
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Packt Publishing, 2019. — 456 p. — ISBN 978-1-78913-636-4. A guide to advances in machine learning for financial professionals, with working Python code. Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms...
  • №235
  • 20,18 МБ
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Packt, 2018. — 503 p. — ISBN 178934641X The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access...
  • №236
  • 36,39 МБ
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Packt, 2018. — 503 p. — ISBN 178934641X. Code files only! The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book...
  • №237
  • 105,83 МБ
  • добавлен
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Packt, 2018. — 503 p. The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental,...
  • №238
  • 24,87 МБ
  • добавлен
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Boston: Kluwer Academic Publishers, 2004. - 220 p. Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it bridges the two schools of...
  • №239
  • 21,47 МБ
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Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN 978-981-10-5151-7. This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its...
  • №240
  • 3,06 МБ
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Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN 978-981-10-5151-7. This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its...
  • №241
  • 9,97 МБ
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Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN 978-981-10-5152-4 (eBook). This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its...
  • №242
  • 13,12 МБ
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Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN 978-981-10-5152-4 (eBook). This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its...
  • №243
  • 34,38 МБ
  • добавлен
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Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN 978-981-10-5152-4 (eBook). This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its...
  • №244
  • 34,55 МБ
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Springer, 2006. — 656. Feature selection and model selection are two major elements in machine learning. Both feature selection and model selection are inherently multi-objective optimization problems where more than one objective has to be optimized. For example in feature selection, minimization of the number of features and maximization of feature quality are two common...
  • №245
  • 6,86 МБ
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Packt, 2019. — 482 p. — ISBN 1789952298. Applied Unsupervised Learning with Python: Discover hidden patterns and relationships in unstructured data with Python Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Key Features Learn how to select the most suitable Python library to solve your problem Compare...
  • №246
  • 10,72 МБ
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Birmingham: Packt Publishing, 2019. — 482 p. — ISBN 1789952298. Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data ! Key Features Learn how to select the most suitable Python library to solve your problem. Compare k-Nearest Neighbor (k-NN) and non-parametric methods and decide when to use them. Delve into the...
  • №247
  • 10,69 МБ
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Birmingham: Packt Publishing, 2019. — 403 p. — ISBN 1789954924. Explore the exciting world of machine learning with the fastest growing technology in the world ! Key Features Understand various machine learning concepts with real-world examples Implement a supervised machine learning pipeline from data ingestion to validation Gain insights into how you can use machine learning in...
  • №248
  • 7,05 МБ
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Packt Publishing, 2019. — 482 p. — ISBN: 978-1-78995-229-2. Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Unsupervised learning is a useful and practical solution in situations where labeled data is not available. Applied Unsupervised Learning with Python guides you on the best practices for using...
  • №249
  • 11,25 МБ
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Packt Publishing, 2019. — 186 p. — ISBN: 978-1-78995-229-2. Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Unsupervised learning is a useful and practical solution in situations where labeled data is not available. Applied Unsupervised Learning with Python guides you on the best practices for using...
  • №250
  • 8,37 МБ
  • добавлен
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Packt Publishing, 2019. — 186 p. — ISBN: 978-1-78995-229-2. Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Unsupervised learning is a useful and practical solution in situations where labeled data is not available. Applied Unsupervised Learning with Python guides you on the best practices for using...
  • №251
  • 10,72 МБ
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Springer, 2020. — 261 p. — ISBN 3030266214. This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI...
  • №252
  • 6,18 МБ
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Birmingham: Packt Publishing, 2018. — 149 p. — ISBN 1789534097. Key Features Clear and concise explanations. Gives important insights into deep learning models. Practical demonstration of key concepts. Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation . This...
  • №253
  • 6,38 МБ
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Springer, 2018. - 525p. - ISBN : 9811312796 This book presents high-quality papers from an international forum for research on computational approaches to learning. It includes current research and findings from various research labs, universities and institutions that may lead to development of marketable products. It also provides solid support for these findings in the form of...
  • №254
  • 22,78 МБ
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Packt Publishing, 2016. — 258 p. — ISBN 978-1-78439-658-9. Design, build, and deploy your own machine learning applications by leveraging key Java machine learning libraries As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning...
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  • 4,45 МБ
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Packt Publishing, 2016. — 258 p. — ISBN 978-1-78439-658-9. Design, build, and deploy your own machine learning applications by leveraging key Java machine learning libraries As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning...
  • №256
  • 4,39 МБ
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Packt Publishing, 2016. — 257 p. — ISBN 10 1784396583, 13 978-1784396589. If you want to learn how to use Java's machine learning libraries to gain insight from your data, this book is for you. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. You should be...
  • №257
  • 4,63 МБ
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Springer, 2019. - 639 p. - ISBN 3030145956. This textbook explains Deep Learning Architecture , with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance,...
  • №258
  • 19,11 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №259
  • 245,00 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №260
  • 245,00 МБ
  • добавлен
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №261
  • 76,12 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №262
  • 245,00 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №263
  • 245,00 МБ
  • добавлен
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №264
  • 245,00 МБ
  • добавлен
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №265
  • 203,77 МБ
  • добавлен
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №266
  • 245,00 МБ
  • добавлен
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №267
  • 55,87 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №268
  • 245,00 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №269
  • 245,00 МБ
  • добавлен
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №270
  • 235,15 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №276
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №278
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №282
  • 245,00 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №283
  • 48,20 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №286
  • 245,00 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
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  • 245,00 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №288
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №289
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №290
  • 155,24 МБ
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Read by author. — Udemy, updated 12/2018. — MP4, video: AVC 1280x720, audio: AAC 44KHz 2 channels . — Duration 12:02:59. — Lec: 92. Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you...
  • №291
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Издательство EPFL Press, 2009, -380 pp. The book is devoted to the analysis, modelling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense, machine learning can be considered a subfield of artificial intelligence; the subject is mainly concerned with the development of techniques and algorithms that allow computers to learn from...
  • №292
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2nd Edition. — Packt Publishing, 2019. — 326 p. — ISBN: 978-1-78899-459-0. Bring magic to your mobile apps using TensorFlow Lite and Core ML Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the...
  • №293
  • 8,12 МБ
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2nd Edition. — Packt Publishing, 2019. — 326 p. — ISBN: 978-1-78899-459-0. Bring magic to your mobile apps using TensorFlow Lite and Core ML Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the...
  • №294
  • 34,25 МБ
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2nd Edition. — Packt Publishing, 2019. — 326 p. — ISBN: 978-1-78899-459-0. Bring magic to your mobile apps using TensorFlow Lite and Core ML Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the...
  • №295
  • 34,23 МБ
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2nd Edition. — Packt Publishing, 2019. — 240 p. — ISBN: 978-1-78899-459-0. Bring magic to your mobile apps using TensorFlow Lite and Core ML Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the...
  • №296
  • 33,79 МБ
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2nd Edition. — Packt Publishing, 2019. — 240 p. — ISBN: 978-1-78899-459-0. Bring magic to your mobile apps using TensorFlow Lite and Core ML Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the...
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  • 3,48 МБ
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New York: Apress, 2018. — 355 p. Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine...
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  • 2,32 МБ
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Apress, 2018. — 355 p. Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with...
  • №299
  • 2,67 МБ
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Apress, 2018. — 355 p. — ISBN 978-1-4842-2987-3. Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the...
  • №300
  • 4,81 МБ
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Pearson, 2019. — 288 p. — ISBN 9780134116556. Foundational Hands-On Skills for Succeeding with Real Data Science Projects This pragmatic book introduces both machine learning and data science, bridging gaps between data scientist and engineer, and helping you bring these techniques into production. It helps ensure that your efforts actually solve your problem, and offers unique...
  • №301
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Addison-Wesley Professional, 2019. — 280 p. Foundational Hands-On Skills for Succeeding with Real Data Science Projects This pragmatic book introduces both machine learning and data science, bridging gaps between data scientist and engineer, and helping you bring these techniques into production. It helps ensure that your efforts actually solve your problem, and offers unique...
  • №302
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O'Reilly Media, 2014. — 234 p. — ISBN: 1449374069, 9781449374068 Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms,...
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Springer, 2018. - 161p. - ISBN : 3030001288 This book constitutes the refereed proceedings of the First International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 17 full papers presented were carefully reviewed and selected from 21 submissions. The papers are organized in the...
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Wiley, 2018. — 352 p. — ISBN 1119439191. An introduction to machine learning that includes the fundamental techniques, methods, and applications. Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author an expert in the field presents fundamental ideas, terminology, and...
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Morgan Kaufmann, 1990. — 815. As the field of machine learning enjoys unprecedented growth and attracts many new researchers, there is a need for regular summaries and comprehensive reviews of its progress. This volume is a sequel to the previous volumes of same title: Volume I appeared in 1983, Volume II in 1986. Volume III presents sample of machine learning research...
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Springer, 2018. — 317 p. — ISBN 978-3319730394. This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines...
  • №307
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Springer, 2018. — 317 p. — ISBN 978-3319730394. This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines...
  • №308
  • 8,39 МБ
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Издательство CRC Press, 2012, -316 pp. "Cost-Sensitive Machine Learning" is one of the first books to provide an overview of the current research efforts and problems in this area. It discusses real-world applications that incorporate the cost of learning into the modeling process. The first part of the book presents the theoretical underpinnings of cost-sensitive machine...
  • №309
  • 21,36 МБ
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Addison-Wesley Professional, 2019. — 871 p. — (Addison-Wesley Data & Analytics Series). — ISBN 0135116694. Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely visual, intuitive, and accessible , and yet offers a comprehensive introduction to...
  • №310
  • 19,74 МБ
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2nd ed. — Springer, 2017. — 348 p. This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees,...
  • №311
  • 3,08 МБ
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New York: Springer, 2020. — 202 p. This book discusses one of the major applications of Artificial Iintelligence (AI): the use of Machine Learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also...
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New York: Springer, 2017. — 138 p. — ISBN 978-3-319-55312-2 This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in...
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Packt Publishing, 2019. — 294 р. — ISBN 978-1788830577. Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right...
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  • 18,51 МБ
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Packt Publishing, 2019. — 294 р. — ISBN 978-1788830577. Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right...
  • №315
  • 26,82 МБ
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Packt, 2019. - 298p. - ISBN: 1789612853 Combine popular machine learning techniques to create ensemble models using Python Key Features Implement ensemble models using algorithms such as random forests and AdaBoost Apply boosting, bagging, and stacking ensemble methods to improve the prediction accuracy of your model Explore real-world data sets and practical examples coded in...
  • №316
  • 4,48 МБ
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Packt, 2019. - 298p. - ISBN: 1789612853 Combine popular machine learning techniques to create ensemble models using Python Key Features Implement ensemble models using algorithms such as random forests and AdaBoost Apply boosting, bagging, and stacking ensemble methods to improve the prediction accuracy of your model Explore real-world data sets and practical examples coded in...
  • №317
  • 5,84 МБ
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Packt Publishing, 2019. — 284 p. — ISBN 978-1-78961-285-1. Combine popular machine learning techniques to create ensemble models using Python Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a...
  • №318
  • 3,88 МБ
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Packt Publishing, 2019. — 386 p. — ISBN 978-1-78961-285-1. Combine popular machine learning techniques to create ensemble models using Python Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a...
  • №319
  • 8,45 МБ
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Packt Publishing, 2019. — 386 p. — ISBN 978-1-78961-285-1. Combine popular machine learning techniques to create ensemble models using Python Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a...
  • №320
  • 4,43 МБ
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Packt Publishing, 2019. — 284 p. — ISBN 978-1-78961-285-1. Code files only! Combine popular machine learning techniques to create ensemble models using Python Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak...
  • №321
  • 239,91 КБ
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Packt Publishing, 2018. — 2014 p. — ISBN 1789138132. !Code files only START READING Book Description Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity About This Book Learn how to apply core machine learning concepts to your games with Unity Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to...
  • №322
  • 266,19 КБ
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Packt Publishing, 2020. — 419 p. — ISBN 978-1-83921-493-6. Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their...
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Packt Publishing, 2020. — 419 p. — ISBN 978-1-83921-493-6. Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their...
  • №324
  • 6,35 МБ
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Packt Publishing, 2020. — 482 p. — ISBN 978-1-83921-493-6. Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their...
  • №325
  • 31,69 МБ
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Packt Publishing, 2020. — 482 p. — ISBN 978-1-83921-493-6. Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their...
  • №326
  • 17,03 МБ
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Packt Publishing, 2020. — 482 p. — ISBN 978-1-83921-493-6. Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their...
  • №327
  • 17,00 МБ
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Packt Publishing, 2020. — 419 p. — ISBN 978-1-83921-493-6. Code files only! Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial...
  • №328
  • 14,99 МБ
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Packt Publishing, 2013. — 396 p. — ISBN: 1782162143, 9781782162148 Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never...
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  • 5,39 МБ
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3rd ed. — Packt, 2019. — 458 p. — ISBN 1788295862. Solve real-world data problems with R and machine learning Key Features Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with a clear, hands-on guide by...
  • №330
  • 28,15 МБ
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2nd Edition. — Packt Publishing, 2015. — 454 p. — ISBN 978-1-78439-390-8 Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has...
  • №331
  • 10,88 МБ
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CRC Press, 2019. — 349 p. На английском языке Промышленное применение машинного обучения показывает, как машинное обучение может применяться для решения реальных проблем в четвертой промышленной революции, и предоставляет необходимые знания и инструменты, позволяющие читателям создавать свои собственные решения на основе теории и практики. Книга знакомит с четвертой промышленной...
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CRC Press, 2019. — 350p. - ISBN: 0815356226 Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its...
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Springer, 2018 (2019 Edition). — 188 p. Deep Learning and Missing Data in Engineering Systems discuss concepts and applications of artificial intelligence, specifically, deep learning. The artificial intelligence techniques that are studied include multilayer autoencoder networks and deep autoencoder networks. Also studied in this book are computational and swarm intelligence...
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Монография CRC Press, 2019. -257 с. На английском языке Обучение усилению для киберфизических систем: с примерами кибербезопасности, вдохновленными недавними разработками в области обучения с подкреплением (RL) и киберфизических систем (CPS). Укорененный в поведенческой психологии, RL является одним из основных направлений машинного обучения. В отличие от других алгоритмов...
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CRC Press, 2019. — 257 p. Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised...
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De Gruyter, 2019. — 537 p. — ISBN 978-3-11-049950-6. This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advanced artificial intelligence....
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Springer, 2020. — 160 p. — ISBN 978-981-13-2386-7. This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a...
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Morgan & Claypool Publishers, 2019. — 160 p. — ISBN: 9781681734408, 9781681734415, 9781681734422. The ubiquitous challenge of learning and decision-making from rank data arises in situations where intelligent systems collect preference and behavior data from humans, learn from the data, and then use the data to help humans make efficient, effective, and timely decisions. Often,...
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Springer, 2018. — 118 p. The ideas introduced in this book explore the relationships among big data, machine learning and granular computing. In many studies, machine learning has been considered as a powerful tool of big data processing. The relationship between big data and machine learning is very similar to the relationship between resources and human learning. In this...
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Birmingham: Packt Publishing, 2019. — 355 p. — ISBN 1789131111. Key Features Learn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasks. Understand and develop model-free and model-based algorithms for building self-learning agents . Work with advanced Reinforcement Learning concepts and algorithms such as imitation learning and evolution...
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Packt Publishing, 2019. — 356 p. — ISBN 978-1-78913-111-6. Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will...
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Packt Publishing, 2019. — 356 p. — ISBN 978-1-78913-111-6. Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will...
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Packt Publishing, 2019. — 356 p. — ISBN 978-1-78913-111-6. Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will...
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Packt Publishing, 2019. — 356 p. — ISBN 978-1-78913-111-6. Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will...
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Packt Publishing, 2019. — 356 p. — ISBN 978-1-78913-111-6. Code files only! Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements....
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New York: John Wiley & Sons, 2018. — 53 p. Are you looking for information to help you with your artificial intelligence deep learning journey? This Deep Learning Dummies guide will help you understand what AI, deep learning and machine learning can mean for you and your organization.
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Wiley-IEEE, 2020. — 474 p. — ISBN 9781119562252. Due to its powerful nonlinear mapping and distribution processing capability, deep NN-based machine learning technology is being considered as a very promising tool to attack the big challenge in wireless communications and networks imposed by the explosively increasing demands in terms of capacity, coverage, latency, efficiency...
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The MIT Press, 2017. — 272 p. — ISBN 0262036827. If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning - programming computers to learn from data - has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer...
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Medium, 2017. — 97 p. This guide is intended to be accessible to anyone . Basic concepts in probability, statistics, programming, linear algebra, and calculus will be discussed, but it isn’t necessary to have prior knowledge of them to gain value from this series. If you're more interested in figuring out which courses to take, textbooks to read, projects to attempt, etc. Take a...
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NY: InfoQ, 2017. — 36 p. Machine learning has long powered many products we interact with daily—from "intelligent" assistants like Apple's Siri and Google Now, to recommendation engines like Amazon's that suggest new products to buy, to the ad ranking systems used by Google and Facebook. More recently, machine learning has entered the public consciousness because of advances in...
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New York: Springer, 2020. — 195 p. This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based...
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Издательство Springer, 2008, -256 pp. The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. With first papers dating back to the 1960’s, DAR is a mature but still growing research field with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the...
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