000 02628cam a22003738i 4500
003 CUTN
005 20240906123920.0
008 191130s2020 enk b 001 0 eng
020 _a9781108470049
020 _a9781108455145
020 _z9781108679930
041 _aEnglish
042 _apcc
082 0 0 _a006.31
_223
_bDEI
100 1 _aDeisenroth, Marc Peter,
100 1 _eauthor.
245 1 0 _aMathematics for machine learning /
_cMarc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong.
260 _aCambridge, United Kingdom :
_bCambridge University Press,
_c2020.
263 _a1912
300 _axvii, 371 pages :
_billustrations (some color) ;
_c26 cm.
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
650 0 _xMathematics.
700 1 _aFaisal, A. Aldo,
700 1 _aOng, Cheng Soon,
700 1 _eauthor.
700 1 _eauthor.
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
942 _2ddc
_cBOOKS
999 _c43464
_d43464