当前位置:主页 > 计算机电子书 > 机器学习 > 机器学习 pdf电子书
understanding-machine-learning-theory-algorithms

understanding-machine-learning-theory-algorithms PDF 英文超清版

  • 更新:2022-02-17
  • 大小:2.48 MB
  • 类别:机器学习
  • 作者:Shalev-Shwartz,、Shai
  • 出版:Cambridge University Press
  • 格式:PDF

  • 资源介绍
  • 学习心得
  • 相关内容

understanding-machine-learning-theory-algorithms》是由Cambridge University Press出版的一本关于机器学习方面的书籍,作者是Shalev-Shwartz,、Shai,主要介绍了关于机器学习、算法方面的知识内容,目前在机器学习类书籍综合评分为:9.4分。

书籍介绍

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.


资源获取

资源地址1:https://pan.baidu.com/s/18P1uDmpu62Q2wqfIXmpEvA(密码:9iiv)

相关资源

网友留言