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:

Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Data Science and Big Data Analytics - EMC Education Services
Artificial Intelligence by example - Denis Rothman
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Python Data Structures and Algorithms - Benjamin Baka
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Deep Learning with Python - Francois Chollet
Machine Learning with spark and python - Michael Bowles
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
An introduction to neural networks - Kevin Gurney & University of Sheffield
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Deep Learning and Neural Networks - Jeff Heaton
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Java Deep Learning Essentials - Yusuke Sugomori
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Deep Learning for Natural Language Processing - Jason Brownlee
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning with Theano - Christopher Bourez
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Learn Keras for Deep Neural Networks - Jojo Moolayil
Neural Networks and Deep Learning - Charu C.Aggarwal
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty