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 Artificial Intelligence Project for Beginners - Joshua Eckroth
An introduction to neural networks - Kevin Gurney & University of Sheffield
Deep Learning for Natural Language Processing - Jason Brownlee
Python Machine Learning - Sebastian Raschka
Artificial Intelligence by example - Denis Rothman
Coding Theory - Algorithms, Architectures and Application
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Deep Learning with Python - Francois Cholletf
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Introduction to Deep Learning - Eugene Charniak
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Neural Networks and Deep Learning - Charu C.Aggarwal
Introduction to the Math of Neural Networks - Jeff Heaton
Python Data Structures and Algorithms - Benjamin Baka
Intelligent Projects Using Python - Santanu Pattanayak
R Deep Learning Essentials - Dr. Joshua F.Wiley
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Medical Image Segmentation Using Artificial Neural Networks
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning with Python - Francois Chollet
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad