| 000 -LEADER |
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| fixed length control field |
nam a22 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230903b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781108455145 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.31 |
| Item number |
DEI |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Deisenroth, Marc Peter |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Mathematics for machine learning |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Cambridge University Press, |
| Date of publication, distribution, etc |
2020 |
| Place of publication, distribution, etc |
Cambridge : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 371 p. ; |
| Other physical details |
ill., |
| Dimensions |
26 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
37.99 |
| Price type code |
GBP |
| Unit of pricing |
110.40 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| 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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Machine learning |
|
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| Topical term or geographic name as entry element |
Mathematics |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Faisal, A. Aldo |
|
|---|
| Personal name |
Ong, Cheng Soon |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |