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:

Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Coding Theory - Algorithms, Architectures and Application
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning in Python - LazyProgrammer
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Fundamentals of Deep Learning - Nikhil Bubuma
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning with Python - Francois Chollet
Amazon Machine Learning Developer Guild Version Latest
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Intelligent Projects Using Python - Santanu Pattanayak
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
The hundred-page Machine Learning Book - Andriy Burkov
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning with Python - Francois Cholletf
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning for Natural Language Processing - Jason Brownlee
Java Deep Learning Essentials - Yusuke Sugomori
Introduction to the Math of Neural Networks - Jeff Heaton
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Machine Learning with spark and python - Michael Bowles
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron