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 Structures and Algorithms - Benjamin Baka
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Introduction to Scientific Programming with Python - Joakim Sundnes
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning in Python - LazyProgrammer
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Pattern recognition and machine learning - Christopher M.Bishop
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Introduction to Deep Learning - Eugene Charniak
An introduction to neural networks - Kevin Gurney & University of Sheffield
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
R Deep Learning Essentials - Dr. Joshua F.Wiley
Python Machine Learning Eqution Reference - Sebastian Raschka
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning with PyTorch - Vishnu Subramanian
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Deep Learning and Neural Networks - Jeff Heaton
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Deep Learning for Natural Language Processing - Jason Brownlee
Deep Learning with Theano - Christopher Bourez
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach