Representation in Machine Learning

Representation in Machine Learning (SpringerBriefs in Computer Science) 1st ed. 2023 Edition
by M. N. Murty (Author), M. Avinash (Author)
Publisher Finelybook 出版社:Springer; 1st ed. 2023 edition (January 21, 2023)
Language 语言:English
pages 页数:102 pages
ISBN-10 书号:9811979073
ISBN-13 书号:9789811979071

Book Description
This book provides a concise but comprehensive guide to representation, which forms the core of Machine Learning (ML). State-of-the-art practical applications involve a number of challenges for the analysis of high-dimensional data. Unfortunately, many popular ML algorithms fail to perform, in both theory and practice, when they are confronted with the huge size of the underlying data. Solutions to this problem are aptly covered in the book.

In addition, the book covers a wide range of representation techniques that are important for academics and ML practitioners alike, such as Locality Sensitive Hashing (LSH), Distance Metrics and Fractional Norms, Principal Components (PCs), Random Projections and Autoencoders. Several experimental results are provided in the book to demonstrate the discussed techniques’ effectiveness.

下载地址 Download2积分,VIP免费,请先 没有帐号? 注 册 一个!
觉得文章有用就打赏一下
未经允许不得转载:finelybook » Representation in Machine Learning

评论 抢沙发

  • 昵称 (必填)
  • 邮箱 (必填)
  • 网址

您的打赏,我们将继续给力更多优质内容

支付宝扫一扫打赏

微信扫一扫打赏