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:

Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Pattern recognition and machine learning - Christopher M.Bishop
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning with Theano - Christopher Bourez
Introduction to the Math of Neural Networks - Jeff Heaton
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
R Deep Learning Essentials - Dr. Joshua F.Wiley
Python Deep Learning Cookbook - Indra den Bakker
Artificial Intelligence by example - Denis Rothman
Introduction to Scientific Programming with Python - Joakim Sundnes
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Learn Keras for Deep Neural Networks - Jojo Moolayil
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Intelligent Projects Using Python - Santanu Pattanayak
The hundred-page Machine Learning Book - Andriy Burkov
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Deep Learning for Natural Language Processing - Jason Brownlee
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Amazon Machine Learning Developer Guild Version Latest
Python Machine Learning Eqution Reference - Sebastian Raschka
Machine Learning with spark and python - Michael Bowles