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Mathematical Problems in Data Science: Theoretical and Practical Methods Li M. Chen Softcover reprint of the original 1st ed. 2015 edition
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Mathematical Problems in Data Science: Theoretical and Practical Methods
Li M. Chen
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.
213 pages, 42 Illustrations, color; 22 Illustrations, black and white; XV, 213 p. 64 illus., 42 illu
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 14 de marzo de 2019 |
| ISBN13 | 9783319797397 |
| Editores | Springer International Publishing AG |
| Páginas | 213 |
| Dimensiones | 150 × 220 × 10 mm · 331 g |
| Lengua | Alemán |
![Cover for Li M. Chen · Digital and Discrete Geometry: Theory and Algorithms (Paperback Book) [Softcover reprint of the original 1st ed. 2014 edition] (2016)](https://imusic.b-cdn.net/images/item/original/629/9783319348629.jpg?li-m-chen-2016-digital-and-discrete-geometry-theory-and-algorithms-paperback-book&class=scaled&v=1589459367)