《TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms》是Bleeding Edge Press出版的圖書，作者是Sam Abrahams，Danijar Hafner，Erik Erwitt。
基本介紹
- 外文名：TensorFlow for Machine Intelligence: A Hands-On Introduction to Learning Algorithms
- 作者：Sam Abrahams、Danijar Hafner、Erik Erwitt
- 出版時間：2016年11月10日
- 出版社：Bleeding Edge Press
- 頁數：298 頁
- ISBN：9781939902450
- 裝幀：Paperback
- 售價：USD 29.99
內容簡介
TensorFlow, a popular library for machine learning, embraces the innovation and community-engagement of open source, but has the support, guidance, and stability of a large corporation. Because of its multitude of strengths, TensorFlow is appropriate for individuals and businesses ranging from startups to companies as large as, well, Google. TensorFlow is currently being used f...(展開全部) TensorFlow, a popular library for machine learning, embraces the innovation and community-engagement of open source, but has the support, guidance, and stability of a large corporation. Because of its multitude of strengths, TensorFlow is appropriate for individuals and businesses ranging from startups to companies as large as, well, Google. TensorFlow is currently being used for natural language processing, artificial intelligence, computer vision, and predictive analytics. TensorFlow, open sourced to the public by Google in November 2015, was made to be flexible, efficient, extensible, and portable. Computers of any shape and size can run it, from smartphones all the way up to huge computing clusters. This book is for anyone who knows a little machine learning (or not) and who has heard about TensorFlow, but found the documentation too daunting to approach. It introduces the TensorFlow framework and the underlying machine learning concepts that are important to harness machine intelligence. After reading this book, you should have a deep understanding of the core TensorFlow API.
