This book is a hands-on introduction to learning algorithms. It is for people who may know a little machine learning (or not) and who may have heard about TensorFlow, but found the documentation too daunting to approach. The learning curve is gentle and you always have some code to illustrate the math step-by-step.

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 starts with the absolute basics of TensorFlow. We found that most tutorials on TensorFlow start by attempting to teach both machine learning concepts and TensorFlow terminology at the same time. Here we first make sure you've had the opportunity to become comfortable with TensorFlow's mechanics and core API before covering machine learning concepts.

本书是关于学习算法的实践性介绍。它是为那些可能知道一点机器学习（或不知道），并且可能听说过TensorFlow，但发现文档太令人生畏而无法接近的人准备的。学习曲线是温和的，而且你总是有一些代码来一步步说明数学。

TensorFlow是一个流行的机器学习库，它拥抱了开源的创新和社区参与，但又有大公司的支持、指导和稳定性。由于其众多的优势，TensorFlow适合于个人和企业，从初创公司到像谷歌这样的大公司。TensorFlow目前正被用于自然语言处理、人工智能、计算机视觉和预测分析。

TensorFlow于2015年11月由谷歌向公众开放，被认为是灵活、高效、可扩展和可移植的。任何形状和大小的计算机都可以运行它，从智能手机一直到巨大的计算集群。本书从TensorFlow的绝对基础知识开始讲起。我们发现，大多数关于TensorFlow的教程开始时都试图同时教授机器学习概念和TensorFlow术语。在这里，我们首先确保你有机会对TensorFlow的机制和核心API感到满意，然后再介绍机器学习的概念。