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:

Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Machine Learning with Python for everyone - Mark E.Fenner
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Amazon Machine Learning Developer Guild Version Latest
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Deep Learning and Neural Networks - Jeff Heaton
R Deep Learning Essentials - Dr. Joshua F.Wiley
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Data Science and Big Data Analytics - EMC Education Services
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Deep Learning with Theano - Christopher Bourez
Deep Learning with PyTorch - Vishnu Subramanian
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Introduction to Deep Learning - Eugene Charniak
Deep Learning for Natural Language Processing - Jason Brownlee
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning in Python - LazyProgrammer
Neural Networks and Deep Learning - Charu C.Aggarwal
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Machine Learning with spark and python - Michael Bowles