Mathematics For Machine Learning (Record no. 38171)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01622nam a22001817a 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 978-1108455145 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 510 PET |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Marc Peter Deisenroth |
| 245 ## - TITLE STATEMENT | |
| Title | Mathematics For Machine Learning |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Cambridge University Press |
| Place of publication | United Kingdom |
| Year of publication | 2020 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | Item Weight : 816 g Dimensions : 17.78 x 2.24 x 25.4 cm |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site. |
| 546 ## - LANGUAGE NOTE | |
| Language note | Language : English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | CSE |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Reference Book |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Damaged status | |
| Not for loan | |
| Withdrawn status | Collection code | Permanent Location | Current Location | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Inventory number | Full call number | Accession Number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Computer Science and Engineering | VAST Central Library | VAST Central Library | S-2/REF-COS | 10/01/2026 | Cosmo Books | 3736.75 | K797 | 510 PET | 38346 | 03/02/2026 | Reference Book |