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:

The hundred-page Machine Learning Book - Andriy Burkov
Machine Learning with Python for everyone - Mark E.Fenner
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Data Science and Big Data Analytics - EMC Education Services
An introduction to neural networks - Kevin Gurney & University of Sheffield
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Neural Networks - A visual introduction for beginners - Michael Taylor
Introduction to Deep Learning - Eugene Charniak
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Python Data Structures and Algorithms - Benjamin Baka
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Artificial Intelligence by example - Denis Rothman
Deep Learning with Theano - Christopher Bourez
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Medical Image Segmentation Using Artificial Neural Networks
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Pro Deep Learning with TensorFlow - Santunu Pattanayak