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:

Deep Learning with Python - Francois Chollet
Python Data Structures and Algorithms - Benjamin Baka
Amazon Machine Learning Developer Guild Version Latest
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Artificial Intelligence by example - Denis Rothman
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Machine Learning with spark and python - Michael Bowles
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python Machine Learning Eqution Reference - Sebastian Raschka
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning with PyTorch - Vishnu Subramanian
Java Deep Learning Essentials - Yusuke Sugomori
Introduction to the Math of Neural Networks - Jeff Heaton
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Learn Keras for Deep Neural Networks - Jojo Moolayil
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python Machine Learning - Sebastian Raschka
Introduction to Scientific Programming with Python - Joakim Sundnes
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Data Science and Big Data Analytics - EMC Education Services
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali