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:

Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Java Deep Learning Essentials - Yusuke Sugomori
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Introduction to the Math of Neural Networks - Jeff Heaton
Python Data Structures and Algorithms - Benjamin Baka
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python Machine Learning Eqution Reference - Sebastian Raschka
Introduction to Scientific Programming with Python - Joakim Sundnes
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
R Deep Learning Essentials - Dr. Joshua F.Wiley
An introduction to neural networks - Kevin Gurney & University of Sheffield
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Learn Keras for Deep Neural Networks - Jojo Moolayil
Medical Image Segmentation Using Artificial Neural Networks
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python Deep Learning Cookbook - Indra den Bakker
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Python Machine Learning - Sebastian Raschka
Deep Learning with Theano - Christopher Bourez
Machine Learning with spark and python - Michael Bowles
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Data Science and Big Data Analytics - EMC Education Services