TensorFlow for Deep Learning – Bharath Ramsundar & Reza Bosagh Zadeh

This book will introduce you to the fundamentals of machine learning through TensorFlow. TensorFlow is Google’s new software library for deep learning that makes it straightforward for engineers to design and deploy sophisticated deep learning architectures. You will learn how to use TensorFlow to build systems capable of detecting objects in images, understanding human text, and predicting the properties of potential medicines. Furthermore, you will gain an intuitive understanding of TensorFlow’s potential as a system for performing tensor calculus and will learn how to use TensorFlow for tasks outside the traditional purview of machine learning.

Importantly, TensorFlow for Deep Learning is one of the first deep learning books written for practitioners. It teaches fundamental concepts through practical examples and builds understanding of machine learning foundations from the ground up. The target audience for this book is practicing developers, who are comfortable with designing software systems, but not necessarily with creating learning systems. At times we use some basic linear algebra and calculus, but we will review all necessary fundamentals. We also anticipate that our book will prove useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.

Related posts:

Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Deep Learning with Theano - Christopher Bourez
Introduction to Deep Learning - Eugene Charniak
Python Deep Learning Cookbook - Indra den Bakker
Python Data Structures and Algorithms - Benjamin Baka
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Artificial Intelligence by example - Denis Rothman
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
The hundred-page Machine Learning Book - Andriy Burkov
Pattern recognition and machine learning - Christopher M.Bishop
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Neural Networks and Deep Learning - Charu C.Aggarwal
An introduction to neural networks - Kevin Gurney & University of Sheffield
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Intelligent Projects Using Python - Santanu Pattanayak
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning for Natural Language Processing - Jason Brownlee
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli