书目名称 | Mathematical Foundations of Data Science |
编辑 | Tomas Hrycej,Bernhard Bermeitinger,Siegfried Hands |
视频video | http://file.papertrans.cn/627/626152/626152.mp4 |
概述 | Offers a presentation structure aligned along key problems.Focuses on approaches supported by mathematical arguments, rather than sole computing experiences.Considers key data science problems and eve |
丛书名称 | Texts in Computer Science |
图书封面 |  |
描述 | This textbook aims to point out the most important principles of data analysis from the mathematical point of view. Specifically, it selected these questions for exploring: Which are the principles necessary to understand the implications of an application, and which are necessary to understand the conditions for the success of methods used? Theory is presented only to the degree necessary to apply it properly, striving for the balance between excessive complexity and oversimplification. Its primary focus is on principles crucial for application success. .Topics and features:.Focuses on approaches supported by mathematical arguments, rather than sole computing experiences.Investigates conditions under which numerical algorithms used in data science operate, and what performance can be expected from them.Considers key data science problems: problem formulation including optimality measure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithms.Examines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problem.Addresses t |
出版日期 | Textbook 2023 |
关键词 | Data Science; Big Data; Statistical Learning; Machine Learning; Deep Learning; Artificial Neural Networks |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-031-19074-2 |
isbn_softcover | 978-3-031-19076-6 |
isbn_ebook | 978-3-031-19074-2Series ISSN 1868-0941 Series E-ISSN 1868-095X |
issn_series | 1868-0941 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |