Packt Publishing, 2021. — 417 p. — ISBN 9781800208865. Master TensorFlow to create powerful machine learning algorithms, with valuable insights on Keras, Boosted Trees, Tabular Data, Transformers, Reinforcement Learning and more Key Features Work with the latest code and examples for TensorFlow 2 Get to grips with the fundamentals including variables, matrices, and data sources...
Packt Publishing, 2019. — 184 p. — ISBN: 1789533589. Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving....
Packt Publishing, 2018. — 96 p. — ISBN: 178953867X. Explore TensorFlow's capabilities to perform efficient deep learning on images Key Features Discover image processing for machine vision Build an effective image classification system using the power of CNNs Leverage TensorFlow’s capabilities to perform efficient deep learning TensorFlow is Google’s popular offering for...
Packt Publishing, 2019. — 217 p. — ISBN: 978-1-83882-385-6. Get to grips with key structural changes in TensorFlow 2.0 TensorFlow is an end-to-end machine learning platform for experts as well as beginners, and its new version, TensorFlow 2.0 (TF 2.0), improves its simplicity and ease of use. This book will help you understand and utilize the latest TensorFlow features. What’s...
Packt Publishing, 2018. — 300 p. With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. You’ll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released....
Packt Publishing, 2016. — 282 p. — ISBN13: 978-1786466587. This book of projects highlights how TensorFlow can be used in different scenarios - this includes projects for training models, machine learning, deep learning, and working with various neural networks. Each project provides exciting and insightful exercises that will teach you how to use TensorFlow and show you how...
Manning, 2020. — 350 p. — ISBN: 9781617296178. Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the...
Packt Publishing, 2018. — 148 p. — ISBN: 978-1789537291. Key Features Focus on neural network and its essential operations Prepare data for a deep learning model and deploy it as an interactive web application, with Flask and a HTTP API Use Keras, a TensorFlow abstraction library Book Description With this book, you'll learn how to train, evaluate and deploy Tensorflow and...
2nd Edition. — Packt Publishing Limited, July 2020. — 180 p. — ISBN: 978-1-80020-121-7. Cut through the noise and get real results with a step-by-step project-based approach to machine learning with TensorFlow and Keras Machine learning gives computers the ability to learn. With each passing day, machine learning is becoming increasingly transformational to businesses and is...
Packt Publishing, 2020. — 267 p. — ISBN 9781838826789. Implement various state-of-the-art architectures, such as GANs and autoencoders, for image generation using TensorFlow 2.x from scratch Key Features Understand the different architectures for image generation, including autoencoders and GANs Build models that can edit an image of your face, turn photos into paintings, and...
Packt Publishing, 2017. — 174 p. — ISBN: 978-1-78728-277-3. This book is your guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data. Dan Van Boxel’s Deep Learning with TensorFlow...
Apress, 2020. — 318 p. — ISBN: 1484262727. Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web...
BPB Publications, 2022. — 418 p. — ISBN: 978-93-91392-222. Work with TensorFlow and Keras for real performance of deep learning Key Features Combines theory and implementation with in-detail use-cases. Coverage on both, TensorFlow 1.x and 2.x with elaborated concepts. Exposure to Distributed Training, GANs and Reinforcement Learning. Description Mastering TensorFlow 2.x is a...
Apress, 2020. — 563 p. — ISBN: 1484253485. Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome...
Packt Publishing, 2018. — 478 p. — ISBN: 1788292065. Build, scale, and deploy deep neural network models using the star libraries in Python TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive...
Packt Publishing, 2018. — 154 p. — ISBN: 978-1789617740. Learn advanced techniques to improve the performance and quality of your predictive models Key Features Use ensemble methods to improve the performance of predictive analytics models Implement feature selection, dimensionality reduction, and cross-validation techniques Develop neural network models and master the basics...
Packt Publishing, 2019. — 460 p. — ISBN: 978-1-78961-555-5. A comprehensive guide to developing neural network-based solutions using TensorFlow 2.0 TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you’ll explore a revamped framework...
Apress Media LLC., 2021. — 339 p. — ISBN13: (electronic): 978-1-4842-6418-8. Build machine learning web applications without having to learn a new language. This book will help you develop basic knowledge of machine learning concepts and applications. You’ll learn not only theory, but also dive into code samples and example projects with TensorFlow.js. Using these skills and...
O’Reilly, 2017. — 581 с. — 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,...
Packt Publishing, 2017. — 274 p. — ISBN: 978-1788390392. Develop a strong background in neural network programming from scratch, using the popular Tensorflow library. Use Tensorflow to implement different kinds of neural networks – from simple feedforward neural networks to multilayered perceptrons, CNNs, RNNs and more. A highly practical guide including real-world datasets and...
Packt Publishing, 2017. — 536 p. — ISBN: 978-1788293594, 1788293592. Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x Key Features Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and...
2nd Edition. — Packt Publishing, 2020. — 603 p. — ISBN: 978-1-83882-341-2. Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write...
Packt Publishing, 2017. — 536 p. Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial...
Packt Publishing, 2019. — 196 p. — ISBN: 178953075X Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks. Key Features Train your own models for effective prediction, using high-level Keras API Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks Get...
O’Reilly Media, 2017. — 242 p. — ISBN: 978-1-491-97851-1. Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision,...
Packt Publishing, 2017. — 304 p. — ISBN: 978-1786462961. Tackle common commercial machine learning problems with Google’s TensorFlow 1.x library and build deployable solutions. About This Book Enter the new era of second-generation machine learning with Python with this practical and insightful guide Set up TensorFlow 1.x for actual industrial use, including high-performance...
Apress, 2020. — 374 p. — ISBN: 1484263723. Machine Learning for Economics and Finance in TensorFlow 2: Deep Learning Models for Research and Industry Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work in economics is concentrated on the identification of causal...
Packt, 2018. — 322 p. — ISBN: 1789132215. TensorFlow Machine Learning Projects: Build 13 real-world projects with advanced numerical computations using the Python ecosystem Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects Key Features Use machine learning and deep learning...
Packt Publishing Ltd., 2020. — 430 p. — ISBN: 978-1-83882-706-9. Apply neural network architectures to build state-of-the-art computer vision applications using the Python programming language Computer vision allows machines to gain human-level understanding to visualize, process, and analyze images and videos. This book focuses on using TensorFlow to help you learn advanced...
Pckt Publishing, 2017. — 552 p. — ISBN: 1788398920. Harness the power of data in your business by building advanced predictive modelling applications with Tensorflow. A quick guide to gaining hands-on experience with deep learning in different domains such as digit, image & text classification Build your own smart, predictive models with TensorFlow using an easy-to-follow...
Packt Publishing, 2018. — 160 p. — ISBN: 1789136911. Learn how to solve real life problems using different methods like logic regression, random forests and SVMs with TensorFlow. Key Features Understand predictive analytics along with its challenges and best practices Embedded with assessments that will help you revise the concepts you have learned in this book Book Description...
Apress, 2021. — 254 p. — ISBN 1484261674, 9781484261675. Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps up...
O’Reilly Media, Inc., 2021. — 342 p. — ISBN 978-1-492-09079-3. 2021-05-07: First Release Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of AI-driven websites. In this guide, author Gant Laborde--Google Developer Expert in machine...
Apress, 2018. — 227 p. — ISBN: 1484235150. Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with...
Packt Publishing, 2021. — 542 p. — ISBN 9781838829131. Get well versed with state-of-the-art techniques to tailor training processes and boost the performance of computer vision models using machine learning and deep learning techniques Key Features Develop, train, and use deep learning algorithms for computer vision tasks using TensorFlow 2.x Discover practical recipes to...
Packt Publishing, 2018. — 320 p. — ISBN: 1788398068. Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high...
2nd Edition. — Manning Publications, 2020. — 454 p. — ISBN 9781617297717. Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives...
2nd Edition. — Manning Publications, 2020. — 471 p. — ISBN: 9781617297717. This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning, and how to utilize the TensorFlow library to rapidly build powerful ML models. You'll learn the basics of regression, classification, and clustering algorithms, applying them...
2nd edition. — Packt, 2018. — 422 p. TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition Skip the theory and get the most out of Tensorflow to build production-ready machine learning models TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this...
Packt Publishing, 2017. — 370 p. ensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis,...
Apress, 2021. — 279 p. — ISBN 9781484266489. Use TensorFlow 2.x with Google’s Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab’s default install of the most current TensorFlow 2.x along with Colab’s easy access to on-demand GPU...
GitforGits, 2023. — 212 р. — ISBN-13: 978-8119177325. Designed with both beginners and professionals in mind, the book is meticulously structured to cover a broad spectrum of concepts, applications, and hands-on practices that form the core of the TensorFlow Developer Certificate exam. Starting with foundational concepts, the book guides you through the fundamental aspects of...
Apress, 2018. — 398 p. Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep...
Packt Publishing, 2019. — 610 p. — ISBN: 978-1-78883-064-5. A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more. Computer vision solutions are becoming increasingly common, making their way in fields such as health, automobile, social media, and robotics. This book will help you explore...
Springer, 2021. — 190 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN 978-3030570767. This sensible book offers an finish-to-finish information to TensorFlow, the main open supply software program library that helps you construct and practice neural networks for deep studying, Natural Language Processing (NLP), speech recognition, and basic predictive...
Independently published, 2018. — 364 p. — ISBN: 1720092257. Tensorflow is the most popular Deep Learning Library out there. It has fantastic graph computations feature which helps data scientist to visualize his designed neural network using TensorBoard. This Machine learning library supports both Convolution as well as Recurrent Neural network. It supports parallel processing...
Packt Publishing, 2018. — 442 p. Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence—from...
Wiley, 2018. — 360 p. — (For Dummies). — ISBN: 1119466210. Become a machine learning pro! Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy–to–follow book on the subject. Inside, you ll find out how...
2nd Edition. — Apress, 2019. — 240 p. — ISBN13: (electronic): 978-1-4842-5407-3. Explore the new Java programming language features and APIs introduced in Java 10 through Java 13. Java 13 Revealed is for experienced Java programmers looking to migrate to Java 13. Author Kishori Sharan begins by covering how to use local variable type inference to improve readability of your...
Manning Publishing, 2018. — 251 p. — ISBN13: 978-1-61729-387-0. Целевая аудитория: опытные разработчики. TensorFlow - это популярная библиотека для машинного обучения, предназначенная для задач создания и тренировки нейросетей. В основном, используется в связке с языком программирования Python, однако существуют реализации и для других языков, среди которых C++, Java, Go и...
Apress, 2020. - 312p. - ISBN: 9781484259665 Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebook instead of a text editor or a regular IDE. You’ll start by learning how to use Jupyter...
Apress, 2020. — 177 p. — ISBN: 9781484255582. Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build...
Independently published, 2021. — 500 p. — ASIN B08YZ1RXB2. While TensorFlow is an incredibly important machine and deep learning library, we also give you an introduction to three others – NumPy, Pandas, and Scikit Learn. I have produced a hands-on guide, with plenty of code examples for you to follow along with Here’s what you will learn: What deep learning is The difference...
Independently published, 2020. — 176 p.— ISBN B08RZ58C8M. Have you ever wondered how machine learning works? These days, machine learning, deep learning and neural nets are common terms and they are here to stay as a part of our everyday language. Machine learning is not the easiest of topics to teach, purely because there is so much to it. Machine learning, deep learning and...
Packt, 2018. — 404 p. — ISBN: 978-1-78883-454-4. Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow. As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the...
Packt Publishing, 2020. — 314 p. — ISBN 1800209142. Use TensorFlow Enterprise with other GCP services to improve the speed and efficiency of machine learning pipelines for reliable and stable enterprise-level deployment Key Features Build scalable, seamless, and enterprise-ready cloud-based machine learning applications using TensorFlow Enterprise Discover how to accelerate the...
O’Reilly Media, Inc., 2021. — 255 p. — ISBN 978-1-492-08918-6. 2021-07-19: First Release This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and...
O’Reilly, 2020. — 520 p. — ISBN: 1492052043. Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny...
Apress, 2020. -630p. - ISBN: 9781484265130 Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations. You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies used to create deep learning models. While some of these technologies are...
2nd ed. — Packt Publishing, 2018. — 484 p. — ISBN: 978-1-78883-110-9. Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow v1.7. Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being...
Packt Publishing, 2017. — 320 p. Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide. Deep learning is the step that comes after machine learning, and has more advanced implementations. Machine learning is not just for academics anymore, but is becoming a mainstream practice...
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