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...
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...
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 a 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...
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 Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts.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...
O’Reilly, 2017. — 581 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,...
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...
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...
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...
GitforGits, 2024. — 212 p. — ASIN: B0CHBPHLMD. 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...
Pckt Publishing, 2017. — 552 p. — ISBN: 1788398920. Harness the power of data in your business by building advanced predictive modeling 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...
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 learning...
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, 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. — 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 p. — 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...
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...
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. — ISBN-13 (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...
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,...
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...
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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