02722cam a22003738i 4500 737 737 21336577 OSt 20251027205724.0 191130s2020 enk b 001 0 eng 2019040762 9781108455145 (paperback) LBSOR/DLC eng rda DLC pcc Q325.5 .D45 2020 006.31 D325 2020 23 Deisenroth, Marc Peter, author. Mathematics for machine learning / Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong. 1912 Cambridge ; New York, NY : Cambridge University Press, 2020. xvii, 371 pages cm text txt rdacontent unmediated n rdamedia volume nc rdacarrier Includes bibliographical references and index. Introduction 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. "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"-- Provided by publisher. Machine learning Mathematics. Faisal, A. Aldo, author. Ong, Cheng Soon, author. Online version: Deisenroth, Marc Peter. Mathematics for machine learning. Cambridge, United Kingdom ; New York : Cambridge University Press, 2020. 9781108679930 (DLC) 2019040763 7 cbc orignew 1 ecip 20 y-gencatlg ddc BK 0 0 ddc 0 0 NFIC CL CL RES 2023-08-01 Purchased (MegaTexts Phil. Inc.) 10566 0 006.31 D325 2020 10566 2023-08-01 2023-08-01 BK