BLGM's mission is to promote a love of books and reading to all by offering advice and information needed to help our visitors to find their next favorite book. We regularly create and post so-called listicles (also known as booklists) on various mostly tech-related topics.

Best Tensorflow Books To Read

In this post, we have prepared a curated top list of reading recommendations for beginners and experienced. This hand-picked list of the best Tensorflow books and tutorials can help fill your brain this April and ensure you’re getting smarter. We have also mentioned the brief introduction of each book based on the relevant Amazon or Reddit descriptions.

1. Hands-On Machine Learning with Scikit-Learn and TensorFlow (2017)

 Best Tensorflow Books To ReadGraphics in this book are printed in black and white. 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 theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain…
Author(s): Aurélien Géron

2. Learning TensorFlow: A Guide to Building Deep Learning Systems (2017)

 Best Tensorflow Books To ReadRoughly 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, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals…
Author(s): Tom Hope, Yehezkel S. Resheff

3. Pro Deep Learning with TensorFlow: A Mathematical Approach to Advanced Artificial Intelligence in Python (2017)

 Best Tensorflow Books To ReadDeploy 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 learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant…
Author(s): Santanu Pattanayak

4. Deep Learning for Beginners: Practical Guide with Python and Tensorflow (Data Sciences) (2017)

 Best Tensorflow Books To ReadIf you are looking for a book to help you understand how the deep learning works by using Python and Tensorflow, then this is a good book for you. Equations are great for really understanding every last detail of an algorithm.  But to get a basic idea of how something works,this book contains several graphs which detail each neural networks and deep learning algorithms. It is contains also several graphs for practical examples. This book will help you explore exactly what deep learning is and will also teach you about why it is so revolutionary and fascinating. The chapters will introduce the reader to the concepts…
Author(s): François Duval

5. Reinforcement Learning (2017)

 Best Tensorflow Books To ReadMaster reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI  before looking at Open…
Author(s): Abhishek Nandy, Manisha Biswas

6. Python Machine Learning (2017)

 Best Tensorflow Books To ReadMachine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka’s bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning…
Author(s): Sebastian Raschka, Vahid Mirjalili

7. TensorFlow for Deep Learning (2018)

 Best Tensorflow Books To ReadLearn how to solve challenging machine learning problems with Tensorflow, Google’s revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to build—and when to use—deep learning architectures. You’ll learn how to design systems capable of detecting objects in images, understanding human speech, analyzing video, and predicting the properties of potential medicines. TensorFlow for Deep Learning teaches concepts through practical examples…
Author(s): Bharath Ramsundar, Reza Bosagh Zadeh

8. TensorFlow Machine Learning Cookbook (2017)

 Best Tensorflow Books To ReadTensorFlow 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, regression analysis, clustering analysis, artificial neural networks, and deep learning each using Google’s machine learning library TensorFlow.
Author(s): Nick McClure

9. Machine Learning with TensorFlow (2018)

 Best Tensorflow Books To ReadMachine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. TensorFlow, Google’s library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine. Machine Learning with TensorFlow gives readers a solid foundation in machine…
Author(s): Nishant Shukla

10. Machine Learning with TensorFlow (2017)

 Best Tensorflow Books To ReadTackle common commercial machine learning problems with Google’s TensorFlow 1.x library and build deployable solutions. This book is for data scientists and researchers who are looking to either migrate from an existing machine learning library or jump into a machine learning platform headfirst. The book is also for software developers who wish to learn deep learning by example. Particular focus is placed on solving commercial deep learning problems from several…
Author(s): Quan Hua, Shams Ul Azeem

11. TensorFlow Deep Learning Cookbook (2017)

 Best Tensorflow Books To ReadTake 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 intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life…
Author(s): Antonio Gulli, Amita Kapoor

12. Getting Started with TensorFlow (2016)

 Best Tensorflow Books To ReadGoogle’s TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks. This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you’ll gain familiarity with the framework and perform the mathematical operations required for data analysis.
Author(s): Giancarlo Zaccone

You might also be interested in: Oculus Rift, Scala, Cassandra, Ruby on Rails, Paypal, Apache Kafka, Angular, ASP.NET MVC, Firebase, Scipy Books.

Best Tensorflow Books to Read

We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some Tensorflow books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.

Deep Learning Pipeline: Building A Deep Learning Model With TensorFlow

Author(s): Hisham El-Amir, Mahmoud Hamdy
ID: 2452069, Publisher: 2020, Year: Apress, Size: 12 Mb, Format: pdf

Machine Learning with TensorFlow

Author(s): Chris A. Mattmann
ID: 2869564, Publisher: Manning Publications, Year: 2021, Size: 23 Mb, Format: pdf

Convolutional Neural Networks with Swift for Tensorflow

Author(s): Brett Koonce
ID: 2875314, Publisher: , Year: 2021, Size: 2 Mb, Format: pdf

Please note that this booklist is not final. Some books are truly record-breakers according to The New York Times, others are written by unknown writers. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant links you could recommend? Drop a comment if you have any feedback on the list.

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