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:

Deep Learning with Applications Using Python - Navin Kumar Manaswi
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Deep Learning with Hadoop - Dipayan Dev
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Introduction to Deep Learning - Eugene Charniak
Python Machine Learning Eqution Reference - Sebastian Raschka
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Data Science and Big Data Analytics - EMC Education Services
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
R Deep Learning Essentials - Dr. Joshua F.Wiley
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Machine Learning with spark and python - Michael Bowles
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Neural Networks - A visual introduction for beginners - Michael Taylor
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Artificial Intelligence by example - Denis Rothman
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Deep Learning with Python - Francois Chollet
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy