October 2020
Intermediate to advanced
693 pages
16h 26m
Chinese
Content preview from 机器学习实战：基于Scikit-Learn、Keras 和TensorFlow （原书第2 版）
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译者序
随着 AlphaGo 在人机大战中一举成名，关于人工智能的研究开始广受关注，人工智能
科学家也一跃成为“21 世纪热门的人才”。人工智能，特别是机器学习和深度神经网络
的广泛应用虽然兴起不久，但是对这两个密切关联的领域的研究其实已经持续了好几十
年，早已形成了系统化的知识体系。对于想要踏入机器学习和深度学习领域的初学者和
工程师而言，一本理论和实践相结合的书籍是必不可少的，本书就是这样一本书。
本书分为两部分：第一部分介绍机器学习的基础知识；第二部分介绍神经网络与深度学
习。附录部分的内容也非常丰富。本书兼顾理论与实战，既适合在校学生，又适合有经
验的工程师。
从理论上讲，本书最大的特色就是有深度，覆盖面广，但是书中并没有太多复杂的数学
公式推导，很容易看懂。这在现在很多机器学习书籍中是不多见的。
从实战来说，本书使用了当前热门的机器学习框架 Scikit-Learn 及深度学习框架 TensorFlow
和 Keras，每一章都配备相应的项目示例，代码的实操性和可读性非常好。本书也是为
有经验的工程师而写的，是一本实用指南。特别是附录 B 给出的机器学习项目清单，如果
工业界想做一套机器学习的解决方案，完全可以按照这个清单去做。
读者朋友可能非常关心第 2 版相比第 1 版有何区别，作者在第 2 版中不仅重写了大部分
章节，还增加了很多机器学习的前沿知识，代码示例采用了 Keras 深度学习框架。
作者将本书所有章节的详细代码都发布在 GitHub 上。项目地址为：
https://github.com/
ageron/handson-ml2
。
译者现在在比利时某科研机构从事深度学习处理器、嵌入式实时人工智能、计算机视觉
和深度学习异构平台上的编程框架等研究工作，虽有多年的机器学习和计算机视觉研究
和开发经验，但本书中所涉及的专业术语与概念较多，部分概念及术语尚无公认的中文 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.