TensorFlow

Packt Publishing, 2019. — 244 p. — ISBN: 978-1-78953-358-3. 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...

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...

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, 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...

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. — ISBN13: (electronic): 978-1-4842-5349-6. Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts.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...

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. — 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, 2019. — 234 p. — ISBN: 978-1-78953-075-9. 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...

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,...

Apress Media LLC., 2020. — 374 p. — ISBN13: (electronic): 978-1-4842-6373-0. 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 relationships in parsimonious statistical models; whereas machine...

Packt Publishing, 2019. — 407 p. — ISBN: 978-1-78913-221-2. Implement TensorFlow’s offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits―simplicity, efficiency, and...

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...

Apress, 2018. — 176 p. — ISBN13: (electronic): 978-1-4842-3516-4. 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...

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...

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...

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...

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...

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 Media LLC, 2020. — 439 p. — ISBN13: (electronic): ISBN: 978-1-4842-5802-6. Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications. Deep learning is quickly integrating itself into the technology...

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...

O’Reilly, 2020. — 479 p. — ISBN: 978-1-492-05204-3. Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size—small enough to work on the digital signal processor in an Android phone. With this practical book, you’ll learn about TensorFlow Lite for Microcontrollers, a miniscule machine...

2nd Edition. — Packt Publishing, 2018. — 508 p. — ISBN: 978-1-78883-110-9. Deep Learning with TensorFlow – Second Edition: Explore neural networks with Python 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...

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...