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:

Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning and Neural Networks - Jeff Heaton
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Machine Learning with spark and python - Michael Bowles
Deep Learning with Python - Francois Cholletf
Artificial Intelligence by example - Denis Rothman
Python Machine Learning Eqution Reference - Sebastian Raschka
Neural Networks and Deep Learning - Charu C.Aggarwal
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Coding Theory - Algorithms, Architectures and Application
Machine Learning with Python for everyone - Mark E.Fenner
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Learn Keras for Deep Neural Networks - Jojo Moolayil
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Medical Image Segmentation Using Artificial Neural Networks
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Fundamentals of Deep Learning - Nikhil Bubuma
Introduction to the Math of Neural Networks - Jeff Heaton
The hundred-page Machine Learning Book - Andriy Burkov
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Deep Learning with PyTorch - Vishnu Subramanian