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
Machine Learning with spark and python - Michael Bowles
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Machine Learning with Python for everyone - Mark E.Fenner
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning in Python - LazyProgrammer
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Artificial Intelligence by example - Denis Rothman
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Neural Networks and Deep Learning - Charu C.Aggarwal
Deep Learning for Natural Language Processing - Jason Brownlee
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Coding Theory - Algorithms, Architectures and Application
Neural Networks - A visual introduction for beginners - Michael Taylor
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
The hundred-page Machine Learning Book - Andriy Burkov
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Python Data Structures and Algorithms - Benjamin Baka
Medical Image Segmentation Using Artificial Neural Networks
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning with Python - Francois Cholletf