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:

Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning in Python - LazyProgrammer
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Python Machine Learning - Sebastian Raschka
Deep Learning with Hadoop - Dipayan Dev
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Data Science and Big Data Analytics - EMC Education Services
Python Deep Learning Cookbook - Indra den Bakker
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning for Natural Language Processing - Jason Brownlee
Neural Networks and Deep Learning - Charu C.Aggarwal
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Artificial Intelligence by example - Denis Rothman
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Deep Learning with Theano - Christopher Bourez
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Coding Theory - Algorithms, Architectures and Application
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Python Machine Learning Eqution Reference - Sebastian Raschka
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Introduction to the Math of Neural Networks - Jeff Heaton