| 书目名称 | Statistical Inference and Machine Learning for Big Data |
| 编辑 | Mayer Alvo |
| 视频video | |
| 概述 | Introduces a comprehensive collection of topics in modern statistical areas.Presents applications to topics in genetics and environmental science.Suitable for upper undergraduate and graduate students |
| 丛书名称 | Springer Series in the Data Sciences |
| 图书封面 |  |
| 描述 | .This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems...The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented...This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.. |
| 出版日期 | Book 2022 |
| 关键词 | big data; machine learning; neural networks; multivariate; nonparametric; symbolic data |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-06784-6 |
| isbn_softcover | 978-3-031-06786-0 |
| isbn_ebook | 978-3-031-06784-6Series ISSN 2365-5674 Series E-ISSN 2365-5682 |
| issn_series | 2365-5674 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 19:45:55
