MATHEMATICS FOR MACHINE LEARNING
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MATHEMATICS FOR MACHINE LEARNING
MATH EMATICS FOR MACHINE LEARNINGContentsForeword1Part I Mathematical Foundations91Introduction and Motivation111.1Finding Words for Intuitions121.2Tw MATHEMATICS FOR MACHINE LEARNING wo Ways to Read This Book131.3Exercises and Feedback162Linear /Algebra172.1Systems of Linear Equations192.2Matrices222.3Solving Systems of Linear Equations272.4Vector Spaces352.5Linear Independence402.6Basis and Rank442.7Linear Mappings482.8Affine Spaces612.9Further Reading Exercises63 643Analytic G MATHEMATICS FOR MACHINE LEARNING eometry'703.1Norms713.2Inner Products723.3Lengths and Distances753.4Angles and Orthogonality763.5Orthonormal Basis783.6Orthogonal Complement793.7InnerMATHEMATICS FOR MACHINE LEARNING
Product of Functions803.8Orthogonal Projections813.9Rotations913.10Further Reading Exercises94 964Matrix Decompositions984.1Determinant and Trace99iTMATH EMATICS FOR MACHINE LEARNINGContentsForeword1Part I Mathematical Foundations91Introduction and Motivation111.1Finding Words for Intuitions121.2Tw MATHEMATICS FOR MACHINE LEARNING Ong (2020). This version is free to view and download for personal use only. Not for re-distribution, re-sale, or use in derivative works. C'by M. p. Dciscnroth, A. A. Faisal, and c. s. Ong. 2021. https://ml-book.coa.iiContents4.2Eigenvalues and Eigenvectors105 MATHEMATICS FOR MACHINE LEARNING MATH EMATICS FOR MACHINE LEARNINGContentsForeword1Part I Mathematical Foundations91Introduction and Motivation111.1Finding Words for Intuitions121.2TwGọi ngay
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