Understanding Machine Learning 新书_图书内容介绍_剧情呢
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Understanding Machine Learning读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 424页 8.3 2020 Cambridge University Press
定价 出版日期 最近访问 访问指数
USD 48.51 2020-02-20 … 2020-03-14 … 23
主题/类型/题材/标签
机器学习,MachineLearning,人工智能,算法,理论,计算机科学,计算机,ML,
作者
Shai Shalev-Shwartz      ISBN:9781107057135    原作名/别名:《》
内容和作者简介
Understanding Machine Learning摘要

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform t...

作者简介

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics, and engineering.

本书后续版本
未发行或暂未收录
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