- 书名:Information Theory for Data Science
- 出版社:KAIST
- 作者:Changho Suh, KAIST, South Korea
- 出版年份:2023
- 电子书格式: pdf
- 简介:This book, “Information Theory for Data Science,” provides a comprehensive exploration of information theory principles as applied to data science. It delves into key concepts like entropy, mutual information, and channel capacity, offering practical applications for data compression, feature selection, and machine learning. Suitable for students and professionals in data science, machine learning, and related fields, this text bridges the gap between theoretical foundations and practical implementation. Written by Changho Suh, this resource is essential for those looking to build a strong foundation in information theory for data science.
- ISBN:9781638281153, 97816
- 下载地址(点击下载):
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