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:

Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning for Natural Language Processing - Jason Brownlee
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Neural Networks - A visual introduction for beginners - Michael Taylor
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
An introduction to neural networks - Kevin Gurney & University of Sheffield
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Neural Networks and Deep Learning - Charu C.Aggarwal
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Machine Learning with Python for everyone - Mark E.Fenner
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning in Python - LazyProgrammer
Deep Learning with Python - Francois Cholletf
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Artificial Intelligence by example - Denis Rothman
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Intelligent Projects Using Python - Santanu Pattanayak
Data Science and Big Data Analytics - EMC Education Services
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Medical Image Segmentation Using Artificial Neural Networks
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper