02221cam a22002658i 4500 TB12047 IN-BhIIT 20260511184323.0 191130s2020 enk b 001 0 eng 9781108455145 (PBK) IN-BhIIT eng 006.31 DEI/M Deisenroth, Marc Peter, Author. 25043 Mathematics for machine learning / by Marc Peter Deisenroth; A. Aldo Faisal and Cheng Soon Ong. New York : Cambridge University Press, 2021. xvii, 371 p. : ill. ; 24 cm. 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"-- Machine learning Mathematics. 25044 Faisal, A. Aldo, Joint author 25045 Ong, Cheng Soon, Joint author 25046 TB 26 14572 14572 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 6 3 006.31 DEI/M TB12050 2026-05-25 09:17:22 2026-05-11 4331.72 2024-12-12 TB 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 3 3 006.31 DEI/M TB12052 2026-05-08 18:16:54 2026-03-05 4331.72 2024-12-12 TB 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 5 1 006.31 DEI/M TB12049 2026-01-19 10:25:45 2025-11-24 4331.72 2024-12-12 TB 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 4 4 006.31 DEI/M TB12048 2026-01-10 16:43:05 2025-09-23 4331.72 2024-12-12 TB 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 0 006.31 DEI/M TB12047 2024-12-12 00:00:00 4331.72 2024-12-12 RES 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 3 4 006.31 DEI/M TB12051 2025-12-08 11:53:15 2025-11-25 4331.72 2024-12-12 TB 0 0 ddc 0 0 SES CLIITBBS CLIITBBS 2024-12-12 49 3162.16 5 4 006.31 DEI/M TB12053 2026-04-22 14:00:16 2026-01-05 4331.72 2024-12-12 TB