Learning TensorFlow: A Guide to Building Deep Learning Systems

by Tom Hope, Yehezkel S. Resheff, Itay Lieder

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audienceófrom data scientists and engineers to students and researchers. Youíll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, youíll know how to build and deploy production-ready deep learning systems in TensorFlow. Get up and running with TensorFlow, rapidly and painlessly Learn how to use TensorFlow to build deep learning models from the ground up Train popular deep learning models for computer vision and NLP Use extensive abstraction libraries to make development easier and faster Learn how to scale TensorFlow, and use clusters to distribute model training Deploy TensorFlow in a production setting

Genres: Technology, Computer Science, Programming, Artificial Intelligence, Reference, Computers

244 pages, Paperback

Published September 11, 2017

Reviews

[Piotr Szybicki · Rating 3 out of 5]

A lot of good examples but there is no way to understend this book without advanced knoledge of ML algoritms.

[Vishwanath · Rating 4 out of 5]

Great read with a mixture of simple and complex topics. As someone with a bare-bones understanding of tensorflow, this book to me serves as a great standalone reference for sample code. Its especially useful if you want to avoid getting lost in the labyrinth of the online tensorflow documentation. Particularly interesting are the chapters on tensorflow serving and the ability to distribute model training. One of those books you can refer again and again to as you gain a better understanding and appreciation of tensorflow.

[Mehdi · Rating 4 out of 5]

A good and quick intro to Tensorflow. I recommended it for Tensorflow users

[Delhi Irc]

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