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:

Introduction to the Math of Neural Networks - Jeff Heaton
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Data Science and Big Data Analytics - EMC Education Services
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
The hundred-page Machine Learning Book - Andriy Burkov
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Deep Learning with PyTorch - Vishnu Subramanian
Deep Learning for Natural Language Processing - Jason Brownlee
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning with Python - Francois Cholletf
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Machine Learning with Python for everyone - Mark E.Fenner
Neural Networks and Deep Learning - Charu C.Aggarwal
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Machine Learning with spark and python - Michael Bowles
Python Data Structures and Algorithms - Benjamin Baka
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Amazon Machine Learning Developer Guild Version Latest
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Pattern recognition and machine learning - Christopher M.Bishop