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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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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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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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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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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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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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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, 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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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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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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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...
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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...
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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, 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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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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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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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. — 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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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....
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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....
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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...
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Apress, 2019. — 405 p. Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial...
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Apress, 2019. — 405 p. — ISBN 978-1-4842-4167-7. Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way...
  • №72
  • 9,55 МБ
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Apress, 2019. — 421 p. — ISBN-13: 978-1-4842-4166-0. Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the...
  • №73
  • 5,07 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...
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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...
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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...
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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...
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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...
  • №78
  • 4,81 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...
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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...
  • №80
  • 17,79 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...
  • №81
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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...
  • №82
  • 7,95 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...
  • №83
  • 3,75 МБ
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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,...
  • №84
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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...
  • №85
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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...
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  • 6,40 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...
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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...
  • №88
  • 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...
  • №89
  • 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...
  • №90
  • 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...
  • №91
  • 693,91 КБ
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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,...
  • №92
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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,...
  • №93
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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...
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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...
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  • 6,13 МБ
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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...
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  • 7,54 МБ
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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...
  • №97
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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...
  • №98
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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...
  • №99
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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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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...
  • №101
  • 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...
  • №102
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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...
  • №103
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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...
  • №104
  • 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...
  • №105
  • 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...
  • №106
  • 4,81 МБ
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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...
  • №107
  • 16,87 МБ
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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,...
  • №108
  • 6,11 МБ
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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...
  • №110
  • 16,13 МБ
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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...
  • №111
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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...
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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,...
  • №113
  • 3,08 МБ
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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...
  • №114
  • 3,23 МБ
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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...
  • №115
  • 266,19 КБ
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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...
  • №116
  • 5,39 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...
  • №117
  • 10,88 МБ
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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....
  • №118
  • 14,17 МБ
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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...
  • №119
  • 2,93 МБ
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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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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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Издательство InTech, 2009, -430 pp. Machine Learning is often referred to as a branch of artificial intelligence which deals with the design and the development of algorithms and techniques that help machines to learn. Hence, it is closely related to various scientific domains as Optimization, Vision, Robotic and Control, Theoretical Computer Science, etc. Based on this,...
  • №122
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Kluwer, 1993. — 341 p. — ISBN 0-7923-9277-9. One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers...
  • №123
  • 17,02 МБ
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Springer, 1983. — 565. The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learning processes is of great significance to fields concerned with understanding intelligence. Such fields include cognitive science, artificial intelligence, information science, pattern recognition,...
  • №124
  • 7,36 МБ
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Petaluma US : Roundtree Press, 2018. — 104 p. Artificial Intelligence Studio at Globant. Many industries are leveraging artificial intelligence (AI) to stay ahead of the curve. As cognitive and AI platforms become smarter, companies are using deep neural networks to give them abilities they didn’t have before. It’s the augmented intelligence revolution, with AI enhancing existing...
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  • 2,36 МБ
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Petaluma US : Roundtree Press, 2018. — 104 p. — ISBN: 978-1-944903-52-7. Artificial Intelligence Studio at Globant. Many industries are leveraging artificial intelligence (AI) to stay ahead of the curve. As cognitive and AI platforms become smarter, companies are using deep neural networks to give them abilities they didn’t have before. It’s the augmented intelligence revolution,...
  • №126
  • 1,93 МБ
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Petaluma US : Roundtree Press, 2018. — 104 p. — ISBN: 978-1-944903-52-7. Artificial Intelligence Studio at Globant. Many industries are leveraging artificial intelligence (AI) to stay ahead of the curve. As cognitive and AI platforms become smarter, companies are using deep neural networks to give them abilities they didn’t have before. It’s the augmented intelligence revolution,...
  • №127
  • 2,51 МБ
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Petaluma US : Roundtree Press, 2018. — 104 p. — ISBN: 978-1-944903-64-0. Artificial Intelligence Studio at Globant. Many industries are leveraging artificial intelligence (AI) to stay ahead of the curve. As cognitive and AI platforms become smarter, companies are using deep neural networks to give them abilities they didn’t have before. It’s the augmented intelligence revolution,...
  • №128
  • 2,50 МБ
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Petaluma US : Roundtree Press, 2018. — 104 p. — ISBN: 978-1-944903-52-7. Artificial Intelligence Studio at Globant. Many industries are leveraging artificial intelligence (AI) to stay ahead of the curve. As cognitive and AI platforms become smarter, companies are using deep neural networks to give them abilities they didn’t have before. It’s the augmented intelligence revolution,...
  • №129
  • 2,51 МБ
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2nd ed. — Packt, 2017. — 501 p. — ISBN 978-1787125933. Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful...
  • №130
  • 15,63 МБ
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John Wiley & Sons, 2016. — 435 p. — (For Dummies). — ISBN: 1119245516, 9781119245513. Your no-nonsense guide to making sense of machine learning. Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on...
  • №131
  • 11,81 МБ
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AI Sciences, 2018 — 190p. — ISBN-13 978-1724417503. This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using...
  • №132
  • 1,94 МБ
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AI Sciences, 2018. — 190 p. — ISBN-13 978-1724417503. This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using...
  • №133
  • 3,73 МБ
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Packt Publishing, 2018. - 378p. - ISBN: 1788838297 Leverage the power of Apple's Core ML to create smart iOS apps Key Features Explore the concepts of machine learning and Apple's Core ML APIs Use Core ML to understand and transform images and videos Exploit the power of using CNN and RNN in iOS applications Book Description Core ML is a popular framework by Apple, with APIs...
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  • 20,08 МБ
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Packt Publishing, 2018. - 378p. - ISBN: 1788838297 Leverage the power of Apple's Core ML to create smart iOS apps Key Features Explore the concepts of machine learning and Apple's Core ML APIs Use Core ML to understand and transform images and videos Exploit the power of using CNN and RNN in iOS applications Book Description Core ML is a popular framework by Apple, with APIs...
  • №135
  • 10,11 МБ
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Heidelberg: O'Reilly, 2018. — 183 S. — ISBN 978-3-96009-052-6. Language: German Machine Learning erreicht beinahe alle Bereiche der Technik und der Gesellschaft. In diesem Buch bekommen Sie die schnellstmögliche Einführung in das äußerst umfangreiche Themengebiet des Machine Learning und der statistischen Datenanalyse. Dabei werden alle wesentlichen Themen abgedeckt und mit...
  • №136
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Amazon Digital Services LLC, 2018. — 54 р. — (Machine Learning for Beginners Book 1). Welcome to the world of machine learning! Are you looking for a foundational book to get you started with the basic concepts of Machine Learning? My book will explain you the basic concepts in ways that are easy to understand. Once you’ve read this book, you’ll have a solid grasp on the core...
  • №137
  • 1,76 МБ
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Amazon Digital Services LLC, 2018. — 54 р. — (Machine Learning for Beginners Book 1). Welcome to the world of machine learning! Are you looking for a foundational book to get you started with the basic concepts of Machine Learning? My book will explain you the basic concepts in ways that are easy to understand. Once you’ve read this book, you’ll have a solid grasp on the core...
  • №138
  • 2,93 МБ
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Amazon Digital Services LLC, 2018. — 54 р. — (Machine Learning for Beginners Book 1). Welcome to the world of machine learning! Are you looking for a foundational book to get you started with the basic concepts of Machine Learning? My book will explain you the basic concepts in ways that are easy to understand. Once you’ve read this book, you’ll have a solid grasp on the core...
  • №139
  • 1,75 МБ
  • добавлен
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2018. — 54 p. Are you looking for a foundational book to get you started with the basic concepts of Machine Learning? My book will explain you the basic concepts in ways that are easy to understand. Once you’ve read this book, you’ll have a solid grasp on the core principles that will make it easier to step to a more advanced book should you want to learn more.
  • №140
  • 2,92 МБ
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Amazon Digital Services LLC, 2018. — 129 p. — ASIN B07F2NYDTH. Smart homes, self-driving cars, Siri, Alexa - some typical examples of how machine learning and artificial intelligence have become part of our daily life. Wouldn't it be cool to understand the concepts behind these complex topics? This book teaches you how to integrate machine learning into your apps. We're going to...
  • №141
  • 5,11 МБ
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Amazon Digital Services LLC, 2018. — 129 p. — ASIN B07F2NYDTH. Smart homes, self-driving cars, Siri, Alexa - some typical examples of how machine learning and artificial intelligence have become part of our daily life. Wouldn't it be cool to understand the concepts behind these complex topics? This book teaches you how to integrate machine learning into your apps. We're going to...
  • №142
  • 2,70 МБ
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Springer, 2010. — 736 p. Machine learning (ML) is one of the most fruitful fields of research currently, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems. From a technological point of view, the world has changed at an unexpected pace; one of the consequences is that it is possible to use high-quality and fast...
  • №143
  • 7,25 МБ
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O'Reilly Media, 2018. — 209 p. — ISBN 10 149199584X, 13 978-1491995846. EPUB (True/HQ) Deep learning doesn't have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook,...
  • №144
  • 9,13 МБ
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Apress, 2017. — 335 p. — ISBN 978-1-4842-2249-2. This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially...
  • №145
  • 9,87 МБ
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Apress, 2017. — 382 p. — ISBN 10 1484222490, 13 978-1484222492 This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews...
  • №146
  • 5,12 МБ
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New York: Packt Publishing, 2016. — 983 p. Learn to solve challenging data science problems by building powerful machine learning models using Python. Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we...
  • №147
  • 8,76 МБ
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New York: Autoedition, 2014. — 261 p. This course will focus on theoretical aspects of Statistical Learning and Sequential Prediction. Until recently, these two subjects have been treated separately within the learning community. The course will follow a unified approach to analyzing learning in both scenarios. To make this happen, we shall bring together ideas from probability...
  • №148
  • 2,48 МБ
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O'Reilly, 2018. — 400 p. — Early Release. With much success already attributed to deep learning, this discipline has started making waves throughout science broadly and the life sciences in particular. With this practical book, developers and scientists will learn how deep learning is used for genomics, chemistry, biophysics, microscopy, medical analysis, drug discovery, and other...
  • №149
  • 4,67 МБ
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2nd ed. — Packt, 2017. — 501 p. — ISBN 978-1787125933. Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful...
  • №150
  • 16,10 МБ
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2nd ed. — Packt, 2017. — 501 p. — ISBN 978-1787125933. True pdf Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most...
  • №151
  • 10,79 МБ
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IGI Global, 2017 - 129 p. Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction. Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative...
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  • 5,59 МБ
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IGI Global, 2017 - 129 p. Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction. Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative...
  • №153
  • 12,07 МБ
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3rd ed. — CRC Press, 2017. — 691 p. — ISBN 1498797601. The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. is a compilation of new and creative data mining techniques, which...
  • №154
  • 7,46 МБ
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Packt Publishing, 2017. — conv 1410 p. — ASIN B076CRXB76. Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical...
  • №155
  • 33,08 МБ
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Packt Publishing, 2017. — conv 1276 p. — ASIN B076CRXB76. Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical...
  • №156
  • 27,22 МБ
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Издательство Springer, 2014, -120 pp. As users or consumers are now demanding smarter devices, intelligent systems are revolutionizing by utilizing machine learning. Machine learning as part of intelligent systems is already one of the most critical components in everyday tools ranging from search engines and credit card fraud detection to stock market analysis. You can train...
  • №157
  • 2,16 МБ
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CreateSpace Independent Publishing Platform, 2017. — 56 p. The Ultimate Beginners Guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple.From smart bulbs to self-driving cars, intelligent machines are becoming ever more prevalent in our day to day lives. The underpinning of this technology is called machine learning, and is the same basic concept that...
  • №158
  • 9,16 МБ
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CreateSpace Independent Publishing Platform, 2017. — 56 p. The Ultimate Beginners Guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple.From smart bulbs to self-driving cars, intelligent machines are becoming ever more prevalent in our day to day lives. The underpinning of this technology is called machine learning, and is the same basic concept that...
  • №159
  • 1,13 МБ
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CreateSpace Independent Publishing Platform, 2017. — 56 p. The Ultimate Beginners Guide For Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple.From smart bulbs to self-driving cars, intelligent machines are becoming ever more prevalent in our day to day lives. The underpinning of this technology is called machine learning, and is the same basic concept that...
  • №160
  • 1,16 МБ
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Cham: Springer International Publishing, 2018. — 353 p. — ISBN 978-3-319-99492-5. This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing the machine learning theory. The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key...
  • №161
  • 18,84 МБ
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CreateSpace Independent Publishing, 2018. — 106. — ISBN 1719528403. Do You Want to Become An Expert Of Machine Learning? Start Getting this Book and Follow My Step by Step Explanations! This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a...
  • №162
  • 1,04 МБ
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CreateSpace Independent Publishing, 2018. — 106. — ISBN 1719528403. Do You Want to Become An Expert Of Machine Learning? Start Getting this Book and Follow My Step by Step Explanations! This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a...
  • №163
  • 1,30 МБ
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CreateSpace Independent Publishing, 2018. — 106. — ISBN 1719528403. Do You Want to Become An Expert Of Machine Learning? Start Getting this Book and Follow My Step by Step Explanations! This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a...
  • №164
  • 1,27 МБ
  • добавлен
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CreateSpace Independent Publishing, 2018. — 106. — ISBN 1719528403. Do You Want to Become An Expert Of Machine Learning? Start Getting this Book and Follow My Step by Step Explanations! This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a...
  • №165
  • 1,58 МБ
  • добавлен
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CreateSpace Independent Publishing, 2018. — 106. — ISBN 1719528403. Do You Want to Become An Expert Of Machine Learning? Start Getting this Book and Follow My Step by Step Explanations! This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a...
  • №166
  • 8,83 МБ
  • добавлен
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Packt Publishing, 2018. — 240 р. — ISBN 978-1789803556. As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm...
  • №167
  • 9,99 МБ
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Springer, 2019. — 320 p. — ISBN 978-3-319-89802-5. The volume of data is rapidly increasing due to the development of the technology of information and communication. This data comes mostly in the form of streams. Learning from this ever-growing amount of data requires flexible learning models that self-adapt over time. In addition, these models must take into account many...
  • №168
  • 3,80 МБ
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Springer, 2019, — 320 p. The volume of data is rapidly increasing due to the development of the technology of information and communication. This data comes mostly in the form of streams. Learning from this ever-growing amount of data requires flexible learning models that self-adapt over time. In addition, these models must take into account many constraints: (pseudo) real-time...
  • №169
  • 6,96 МБ
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Wiley, 2014. — 256 — ISBN 111836208X. There are a number of algorithms that are typically used for system identification, adaptive control, adaptive signal processing, and machine learning. These algorithms all have particular similarities and differences. However, they all need to process some type of experimental data. How we collect the data and process it determines the most...
  • №170
  • 12,65 МБ
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Wiley, 2014. — 256 — ISBN 111836208X. There are a number of algorithms that are typically used for system identification, adaptive control, adaptive signal processing, and machine learning. These algorithms all have particular similarities and differences. However, they all need to process some type of experimental data. How we collect the data and process it determines the most...
  • №171
  • 13,37 МБ
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The MIT Press, 2018. — 352 р. How deep learning — from Google Translate to driverless cars to personal cognitive assistants — is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on...
  • №172
  • 23,55 МБ
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The MIT Press, 2018. — 352 p. — ISBN-13: 978-0-2620-3803-4. How deep learning — from Google Translate to driverless cars to personal cognitive assistants — is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous...
  • №173
  • 5,17 МБ
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2018. —374p. — ISBN 1138492698. This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.
  • №174
  • 24,66 МБ
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Packt Publishing, 2018. — 282 p. Automate data and model pipelines for faster machine learning applications AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create...
  • №175
  • 5,78 МБ
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Packt Publishing, 2018. — 282 p. Automate data and model pipelines for faster machine learning applications AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create...
  • №176
  • 5,67 МБ
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Packt Publishing, 2018. — 282 p. Automate data and model pipelines for faster machine learning applications AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create...
  • №177
  • 5,47 МБ
  • добавлен
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Packt Publishing, 2018. — 282 p. Automate data and model pipelines for faster machine learning applications AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create...
  • №178
  • 11,29 МБ
  • добавлен
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Packt Publishing, 2018. — 282 p. Automate data and model pipelines for faster machine learning applications AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create...
  • №179
  • 2,01 МБ
  • добавлен
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Springer, 2016. — 345 p. — ISBN: 978-3-319-17289-7, e-ISBN: 978-3-319-17290-3. Machine learning stands as an important research area that aims at developing computational methods capable of improving their performances with previously acquired experiences. Although a large amount of machine learning techniques has been proposed and successfully applied in real systems, there...
  • №180
  • 5,13 МБ
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Amazon Digital Services, 2017. — 61 p. This book is an introduction to basic machine learning and artificial intelligence. It gives you a list of applications, and also a few examples of the different types of machine learning. Here's What You'll Learn in this Book: – Introduction to Machine Learning – Different Applications of Machine Learning – Introduction to Statistics for...
  • №181
  • 10,09 МБ
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Amazon Digital Services, 2017. — 61 p. This book is an introduction to basic machine learning and artificial intelligence. It gives you a list of applications, and also a few examples of the different types of machine learning. Here's What You'll Learn in this Book: – Introduction to Machine Learning – Different Applications of Machine Learning – Introduction to Statistics for...
  • №182
  • 194,21 КБ
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Manning Publications, 2018. — 253 p. Machine learning applications autonomously reason about data at massive scale. It’s important that they remain responsive in the face of failure and changes in load. But machine learning systems are different than other applications when it comes to testing, building, deploying, and monitoring. teaches readers how to implement reactive design...
  • №183
  • 5,76 МБ
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Manning Publications, 2018. — 224 p. — ISBN 978-1-6172-9333-7. Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. Foreword by Sean Owen, Director of Data Science, Cloudera About the Technology If you're building machine...
  • №184
  • 4,60 МБ
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Manning Publications, 2018. — 224 p. Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. Foreword by Sean Owen, Director of Data Science, Cloudera About the Technology If you're building machine learning models to be used...
  • №185
  • 10,60 МБ
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Manning Publications, 2018. — 275 p. — ISBN: 9781617293337. — MEAP version 11 Manning Early Access Program (MEAP). MEAP began February 2016. Publication in February 2018 (estimated). Reactive Machine Learning Systems teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. This example-rich guide...
  • №186
  • 5,76 МБ
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AI Sciences LLC, 2018. — 184 p. — ASIN B07G4M16JF. Are you thinking of learning more about Machine Learning using Python? This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you...
  • №187
  • 2,21 МБ
  • добавлен
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AI Sciences LLC, 2018. — 184 p. — ASIN B07G4M16JF. Are you thinking of learning more about Machine Learning using Python? This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you...
  • №188
  • 4,15 МБ
  • добавлен
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Massachusetts Institute of Technology, Neural Information Processing Series, 2012. — 512 p. ISBN: 026201646X, 978-0262016469. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from...
  • №189
  • 2,98 МБ
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NY: InfoQ, 2018. — 40 p. Machine learning (ML) and deep-learning technologies like Apache Spark, Flink, Microsoft CNTK, TensorFlow, and Caffe brought data analytics to the developer community. Whether it's classifying 2 million sales products received from over 700 multinational retailers for the "Love the Sales" website, building awareness of hindsight bias with customers at...
  • №190
  • 5,45 МБ
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Chapman and Hall/CRC, 2017. — 364 p. — (Machine Learning & Pattern Recognition). — ISBN-10 1138626783; ISBN-13 978-1138626782. Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn’t prove theorems,...
  • №191
  • 7,50 МБ
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Morgan Kaufmann Publishers, 2016. — 524 p. — ISBN: 9780128021217 Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech...
  • №192
  • 18,26 МБ
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MIT Press, 2012. — 263 p. As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the assumption that the data generation mechanism does not change over time. Yet real-world applications of machine learning, including image recognition, natural...
  • №193
  • 12,10 МБ
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Springer, 2019. — 155 p. — ISBN 981133028X This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating...
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  • 2,29 МБ
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Springer, 2019. — 155 p. — ISBN 981133028X This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating...
  • №195
  • 7,23 МБ
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Springer, 2016. — 364 p. Data science is one of the emerging fields in the twenty-first century. This field has been created to address the big data problems encountered in the day-to-day operations of many industries, including financial sectors, academic institutions, information technology divisions, health care companies, and government organizations. One of the important...
  • №196
  • 5,02 МБ
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Packt Publishing, 2018. — 566 p. — ISBN 1788390040. Practical, hands-on solutions in Python to overcome any problem in Machine Learning Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex...
  • №197
  • 42,81 МБ
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Packt Publishing, 2018. — 566 p. — ISBN 1788390040. Practical, hands-on solutions in Python to overcome any problem in Machine Learning Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex...
  • №198
  • 69,74 МБ
  • добавлен
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Scatterplot Press, 2018. — 121 p. Learn How to Make Your Own Recommender System in an Afternoon. Recommender systems are one of the most visible applications of machine learning and data mining today and their uncanny ability to convert our unspoken actions into presenting items we desire is both addicting and concerning. And whether recommender systems excite or scare you, the...
  • №199
  • 3,21 МБ
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Scatterplot Press, 2018. — 121 p. Learn How to Make Your Own Recommender System in an Afternoon. Recommender systems are one of the most visible applications of machine learning and data mining today and their uncanny ability to convert our unspoken actions into presenting items we desire is both addicting and concerning. And whether recommender systems excite or scare you, the...
  • №200
  • 1,56 МБ
  • добавлен
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Scatterplot Press, 2018. — 121 p. Learn How to Make Your Own Recommender System in an Afternoon. Recommender systems are one of the most visible applications of machine learning and data mining today and their uncanny ability to convert our unspoken actions into presenting items we desire is both addicting and concerning. And whether recommender systems excite or scare you, the...
  • №201
  • 1,50 МБ
  • добавлен
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2018. — 204 p. Artificial Intelligence is changing our lives, and solutions based on Deep Learning are leading this transformation. Deep Learning is now of major interest to private companies, since it can be applied to many areas of activity. But getting started in this technology is not an easy task. Many enthusiastic professionals in the field of Deep Learning have difficulties...
  • №202
  • 3,15 МБ
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2018. — 204 p. Artificial Intelligence is changing our lives, and solutions based on Deep Learning are leading this transformation. Deep Learning is now of major interest to private companies, since it can be applied to many areas of activity. But getting started in this technology is not an easy task. Many enthusiastic professionals in the field of Deep Learning have difficulties...
  • №203
  • 6,94 МБ
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Packt Publishing, 2017. — 570 p. — ISBN 9781785280511. Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge....
  • №204
  • 16,28 МБ
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Packt Publishing, 2017. — 570 p. — ISBN 9781785280511. Building Machine Learning applications with R. Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data...
  • №205
  • 14,00 МБ
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Packt Publishing, 2017. — 570 p. — ISBN 9781785280511. Building Machine Learning applications with R. Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data...
  • №206
  • 30,05 МБ
  • добавлен
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Coolbullet Publishing, 2018. — 61 p. — ASIN B07JB516BF. This book will describe step by step, how to take a dataset and create a machine learning model and deploy this to a web application. Do you want to start building Machine Learning Models without having to wade through lots of theoretical equation dense, lengthy textbooks? Then read this book. This book is a practical text,...
  • №207
  • 638,69 КБ
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Morgan & Claypool, 2018. — 169 p. The increasing abundance of large high-quality datasets, combined with significant technical advances over the last several decades have made machine learning into a major tool employed across a broad array of tasks including vision, language, finance, and security. However, success has been accompanied with important new challenges: many...
  • №208
  • 1,20 МБ
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Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
  • №209
  • 15,06 МБ
  • добавлен
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Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
  • №210
  • 24,87 МБ
  • добавлен
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Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
  • №211
  • 11,76 МБ
  • добавлен
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Packt Publishing, 2017. — 304 p. — ISBN 1785882104. Build simple, maintainable, and easy to deploy machine learning applications The mission of this book is to turn readers into productive, innovative data analysts who leverage Go to build robust and valuable applications. To this end, the book clearly introduces the technical aspects of building predictive models in Go, but it...
  • №212
  • 6,32 МБ
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Apress, 2018. - 392p. - ISBN: 1484239504 Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You...
  • №213
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Apress, 2018. - 392p. - ISBN: 1484239504 Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You...
  • №214
  • 14,13 МБ
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© 2005 by Elsevier Inc. Part I Machine learning tools and techniques. What’s it all about? nput: Concepts, instances, and attributes. Output: Knowledge representation. Algorithms: The basic methods. Credibility: Evaluating what’s been learned. mplementations: Real machine learning schemes. Transformations: Engineering the input and output. Moving on: Extensions and...
  • №215
  • 5,17 МБ
  • дата добавления неизвестна
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ITexLi, 2017. — 446 p. — ISBN 953-307-033-1. The goal of this book is to present the key algorithms, theory and applications that from the core of machine learning. Learning is a fundamental activity. It is the process of constructing a model from complex world. And it is also the prerequisite for the performance of any new activity and, later, for the improvement in this...
  • №216
  • 25,06 МБ
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Packt Publishing, 2015. — 405 p. — ISBN-13: 978-1783982042. About This Book Apply R to simplify predictive modeling with short and simple code Use machine learning to solve problems ranging from small to big data Build a training and testing dataset from the churn dataset,applying different classification methods. Who This Book Is For If you want to learn how to...
  • №217
  • 11,01 МБ
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Packt Publishing, 2015. — 405 p. — ISBN-13: 978-1783982042. About This Book Apply R to simplify predictive modeling with short and simple code Use machine learning to solve problems ranging from small to big data Build a training and testing dataset from the churn dataset,applying different classification methods. Who This Book Is For If you want to learn how to...
  • №218
  • 11,70 МБ
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Packt Publising, 2015. — 405 p. — ISBN-13: 978-1783982042. About This Book Apply R to simplify predictive modeling with short and simple code Use machine learning to solve problems ranging from small to big data Build a training and testing dataset from the churn dataset,applying different classification methods. Who This Book Is For If you want to learn how to...
  • №219
  • 8,03 МБ
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Издательство Idea Group, 2007, -384 pp. Machine learning is the study of how to build computer programs that improve their performance at some task through experience. The hallmark of machine learning is that it results in an improved ability to make better decisions. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not...
  • №220
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Издательство InTech, 2010, -288 pp. In recent years many successful machine learning applications have been developed, ranging from data mining programs that learn to detect fraudulent credit card transactions, to information filtering systems that learn user’s reading preferences, to autonomous vehicles that learn to drive on public highways. At the same time, machine...
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Издательство InTech, 2010, -446 pp. The goal of this book is to present the key algorithms, theory and applications that from the core of machine learning. Learning is a fundamental activity. It is the process of constructing a model from complex world. And it is also the prerequisite for the performance of any new activity and, later, for the improvement in this performance....
  • №222
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InTech, 2010, — 374 p. The purpose of this book is to provide an up-to-data and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call Learning tasks, as we use the word in daily life. It is also broad enough to encompass computer that improve from experience in quite...
  • №223
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O'Reilly, 2015. — 59 p. Data science today is a lot like the Wild West: there’s endless opportunity and excitement, but also a lot of chaos and confusion. If you’re new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming. Now you have help. With this O’Reilly report, machine-learning expert Alice Zheng takes you through...
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New York: Springer, 2018. — 485 p. With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for...
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  • 14,23 МБ
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СПб.: Питер, 2017. — 336 с. — (Библиотека программиста). — ISBN 978-5-496-02989-6. Данная книга рассчитана на тех, кто хочет решать самые разнообразные задачи при помощи машинного обучения. Как правило, для этого нужен Python, поэтому в примерах кода используется этот язык, а также библиотеки pandas и scikit-learn. Вы познакомитесь с основными понятиями ML, такими как сбор данных,...
  • №226
  • 60,93 МБ
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СПб.: Питер, 2017. — 336 с. — (Библиотека программиста). — ISBN 978-5-496-02989-6. Данная книга рассчитана на тех, кто хочет решать самые разнообразные задачи при помощи машинного обучения. Как правило, для этого нужен Python, поэтому в примерах кода используется этот язык, а также библиотеки pandas и scikit-learn. Вы познакомитесь с основными понятиями ML, такими как сбор данных,...
  • №227
  • 5,32 МБ
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Учебное пособие. Теория + Практикум (листинги) / В.В. Воронина, А. В. Михеев, Н. Г. Ярушкина, К. В. Святов. — Ульяновск : УлГТУ, 2017. — 290 с. Учебное пособие рассматривает вопросы, связанные с анализом данных: модели, алгоритмы, методы и их реализацию на языке Python. Особое внимание уделено анализу временных рядов. Книга предназначена для студентов группы направлений 09, а...
  • №228
  • 3,63 МБ
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М.: МЦНМО, 2013. — 390 с. Предназначено для первоначального знакомства с математическими основами современной теории машинного обучения (Machine Learning) и теории игр на предсказания. В первой части излагаются основы статистической теории машинного обучения, рассматриваются задачи классификации и регрессии с опорными векторами, теория обобщения и алгоритмы построения разделяющих...
  • №229
  • 2,44 МБ
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М.: МЦНМО, 2013. — 390 с. Книга предназначена для первоначального знакомства с математическими основами современной теории машинного обучения (Machine Learning) и теории игр с предсказаниями. В первой части излагаются основы статистической теории машинного обучения, рассматриваются задачи классификации и регрессии с опорными векторами, теория обобщения и алгоритмы построения...
  • №230
  • 1,78 МБ
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М.: Манн, Иванов и Фербер, 2016. — 336 с. — ISBN 978-5-00100-172-0. Популярная и интересная книга о поиске универсального самообучающегося алгоритма от ученого-практика. Алгоритмы управляют нашей жизнью. Они находят книги, фильмы, работу и партнеров для нас, управляют нашими инвестициями и разрабатывают новые лекарства. Эти алгоритмы все больше обучаются на основе тех...
  • №231
  • 4,37 МБ
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Симферополь: Диайпи, 2014. — 228 с. — ISBN 978–966–491–534–9. В книге рассматриваются теоретические аспекты машинного обучения классификации. В центре изложения — обучаемость как способность применяемых алгоритмов обеспечивать эмпирическое обобщение. С обучаемостью непосредственно связаны вопросы сложности выборок, точности и надежности классификаторов. Большое внимание уделено...
  • №232
  • 5,82 МБ
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М.: ДМК Пресс, 2018. — 252 с. Н2О - простая в использовании и открытая библиотека, которая поддерживает большое количество операционных систем и языков программирования, а также масштабируется для обработки больших данных. Эта книга научит вас использовать алгоритмы машинного обучения, реализованные в Н2О, с упором на наиболее важные для продуктивной работы аспекты. Рассмотрены...
  • №233
  • 121,19 МБ
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М.: O'Reilly Media, 2017. — 392 с. Машинное обучение стало неотъемлемой частью различных коммерческих и исследовательских проектов, однако эта область не является прерогативой больших компаний с мощными аналитическими командами. Даже если вы еще новичок в использовании Python, эта книга познакомит вас с практическими способами построения систем машинного обучения. При всем...
  • №234
  • 13,28 МБ
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СПб.: Питер, 2018. — 585 c. — ISBN 978-5-496-03068-7. Книга "Python Data Science Handbook" - это подробное руководство по самым разным вычислительным и статистическим методам, без которых немыслима любая интенсивная обработка данных, научные исследования и передовые разработки.
  • №235
  • 21,62 МБ
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М.: ДМК Пресс, 2017. — 418 с.: ил. — ISBN 978-5-97060-409-0. Книга предоставит вам доступ в мир прогнозной аналитики и продемонстрирует, почему Python является одним из лидирующих языков науки о данных. Охватывая широкий круг мощных библиотек Python, в том числе scikit-learn, Theano и Keras, предлагая руководство и советы по всем вопросам, начиная с анализа мнений и заканчивая...
  • №236
  • 149,79 МБ
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М.: ДМК Пресс, 2015. — 400 с. Один из самых интересных учебников по машинному обучению - разделу искусственного интеллекта, изучающего методы построения моделей, способных обучаться, и алгоритмов для их построения и обучения. Автор воздал должное невероятному богатству предмета и не упустил из виду объединяющих принципов. Читатель с первых страниц видит машинное обучение в...
  • №237
  • 38,94 МБ
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Пер. с англ. А. А. Слинкина. - М.: ДМК Пресс, 2015.-400 с: ил. ISBN 978-5-97060-273-7, 600 dpi, OCR. Перед вами один из самых интересных учебников по машинному обучению - разделу искусственного интеллекта, изучающего методы построения моделей, способных обучаться, и алгоритмов для их построения и обучения. Автор воздал должное невероятному богатству предмета и не упустил из виду...
  • №238
  • 23,97 МБ
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СПб.: Питер, 2018. — 400 с.: ил. — (Библиотека программиста). — ISBN 978-5-4461-0770-4. Глубокое обучение — Deep learning — это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком обучении...
  • №239
  • 4,42 МБ
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СПб.: Питер, 2018. — 400 с.: ил. — (Библиотека программиста). — ISBN 978-5-4461-0770-4. Глубокое обучение — Deep learning — это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком обучении...
  • №240
  • 10,32 МБ
  • добавлен
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