| 书目名称 | Mathematical Problems in Data Science | | 副标题 | Theoretical and Prac | | 编辑 | Li M. Chen,Zhixun Su,Bo Jiang | | 视频video | | | 概述 | Explains the most current methods for solving cutting edge problems in data science and big data.Provides problem solving techniques and case studies.Covers a wide range of mathematical problems in da | | 图书封面 |  | | 描述 | .This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book includes possible solutions and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets and partial-connectedness among data points or data sets. Discussions also cover the completion problem of Netflix matrix; machine learning method on massive data sets; image segmentation and video search. This book introduces software tools for data science and Big Data such MapReduce, Hadoop, and Spark. ..This book contains three parts. The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematic | | 出版日期 | Book 2015 | | 关键词 | Data science; Big data; Cloud data computing; Data modeling; Data relations; Data connectivity; Geometric | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-25127-1 | | isbn_softcover | 978-3-319-79739-7 | | isbn_ebook | 978-3-319-25127-1 | | copyright | Springer International Publishing Switzerland 2015 |
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发表于 2025-3-21 19:30:10
