| 000 | 02559cam a22003378i 4500 | ||
|---|---|---|---|
| 001 | 21336577 | ||
| 003 | OSt | ||
| 005 | 20241129120358.0 | ||
| 008 | 191130s2020 enk b 001 0 eng | ||
| 010 | _a 2019040762 | ||
| 020 |
_a9781108455145 _q(paperback) |
||
| 040 |
_aLBSOR/DLC _beng _erda _cIISERB |
||
| 042 | _apcc | ||
| 050 | 0 | 0 |
_aQ325.5 _b.D45 2020 |
| 082 | 0 | 0 |
_a006.31 D368M _223 |
| 100 | 1 |
_aDeisenroth, Marc Peter. _930600 |
|
| 245 | 1 | 0 |
_aMathematics for machine learning _cMarc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong. |
| 260 |
_aCambridge: _bCambridge University Press, _c2021. |
||
| 263 | _a1912 | ||
| 300 | _axvii, 371 p. | ||
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | _aIntroduction and motivation -- Linear algebra -- Analytic geometry -- Matrix decompositions -- Vector calculus -- Probability and distribution -- Continuous optimization -- When models meet data -- Linear regression -- Dimensionality reduction with principal component analysis -- Density estimation with Gaussian mixture models -- Classification with support vector machines. | |
| 520 | _a"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 | 0 |
_aMachine learning _xMathematics. _930601 |
|
| 700 | 1 |
_aFaisal, A. Aldo. _930602 |
|
| 700 | 1 |
_aOng, Cheng Soon. _930603 |
|
| 776 | 0 | 8 |
_iOnline version: _aDeisenroth, Marc Peter. _tMathematics for machine learning. _dCambridge, United Kingdom ; New York : Cambridge University Press, 2020. _z9781108679930 _w(DLC) 2019040763 |
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
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| 999 |
_c10392 _d10392 |
||