Learning TensorFlow

Product Description

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 Tensor Flow the leading open source software library that helps you build & train neural networks for computer vision natural language processing (NLP) speech recognition & general predictive analytics Authors Tom Hope Yehezkel Resheff & Itay Lieder provide a hands-on approach to Tensor Flow fundamentals for a broad technical audience-from data scientists & engineers to students & researchers You'll begin by working through some basic examples in Tensor Flow before diving deeper into topics such as neural network architectures Tensor Board visualization Tensor Flow abstraction libraries & multithreaded input pipelines Once you finish this book you'll know how to build & deploy production-ready deep learning systems in Tensor Flow Get up & running with Tensor Flow rapidly & painlessly Learn how to use Tensor Flow to build deep learning models from the ground up Train popular deep learning models for computer vision & NLP Use extensive abstraction libraries to make development easier & faster Learn how to scale Tensor Flow & use clusters to distribute model training Deploy Tensor Flow in a production setting