"This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book."--  Read more...

Abstract: "This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book."

"这本简编对机器学习和数据挖掘领域的数学分析进行了独立的介绍。计算机科学专业学生的典型数学课程中的数学分析部分忽略了这些非常重要的思想和技术，而这些思想和技术对于接近以优化为中心的机器学习专业领域是不可或缺的，如支持向量机、神经网络、各种类型的回归、特征选择和聚类。本书对研究人员和研究生具有特殊的意义，他们将从书中讨论的这些应用领域中受益。"--阅读全文...

摘要："本汇编对机器学习和数据挖掘领域的数学分析进行了自成体系的介绍。计算机科学专业学生的典型数学课程中的数学分析部分忽略了这些非常重要的思想和技术，而这些思想和技术对于接近以优化为中心的机器学习的专业领域是不可或缺的，如支持向量机、神经网络、各种类型的回归、特征选择和聚类。本书对研究人员和研究生特别有意义，他们将从书中讨论的这些应用领域中受益"。