03018nam 2200433 450 99647576260331620221204134625.09789811904011(electronic bk.)9789811904004(MiAaPQ)EBC6986761(Au-PeEL)EBL6986761(CKB)22371876200041(PPN)269151966(EXLCZ)992237187620004120221204d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierKernel methods for machine learning with math and python 100 exercises for building logic /Joe SuzukiGateway East, Singapore :Springer,[2022]©20221 online resource (216 pages)Print version: Suzuki, Joe Kernel Methods for Machine Learning with Math and Python Singapore : Springer,c2022 9789811904004 Includes bibliographical references and index.Intro -- Preface -- How to Overcome Your Kernel Weakness -- What Makes KMMP Unique? -- Acknowledgments -- Contents -- 1 Positive Definite Kernels -- 1.1 Positive Definiteness of a Matrix -- 1.2 Kernels -- 1.3 Positive Definite Kernels -- 1.4 Probability -- 1.5 Bochner's Theorem -- 1.6 Kernels for Strings, Trees, and Graphs -- Appendix -- Exercises 1 sim 15 -- 2 Hilbert Spaces -- 2.1 Metric Spaces and Their Completeness -- 2.2 Linear Spaces and Inner Product Spaces -- 2.3 Hilbert Spaces -- 2.4 Projection Theorem -- 2.5 Linear Operators -- 2.6 Compact Operators -- Appendix: Proofs of Propositions -- Exercises 16 sim 30 -- 3 Reproducing Kernel Hilbert Space -- 3.1 RKHSs -- 3.2 Sobolev Space -- 3.3 Mercer's Theorem -- Appendix -- Exercises 31 sim 45 -- 4 Kernel Computations -- 4.1 Kernel Ridge Regression -- 4.2 Kernel Principle Component Analysis -- 4.3 Kernel SVM -- 4.4 Spline Curves -- 4.5 Random Fourier Features -- 4.6 Nyström Approximation -- 4.7 Incomplete Cholesky Decomposition -- Appendix -- Exercises 46 sim 64 -- 5 The MMD and HSIC -- 5.1 Random Variables in RKHSs -- 5.2 The MMD and Two-Sample Problem -- 5.3 The HSIC and Independence Test -- 5.4 Characteristic and Universal Kernels -- 5.5 Introduction to Empirical Processes -- Appendix -- Exercises 65 sim83 -- 6 Gaussian Processes and Functional Data Analyses -- 6.1 Regression -- 6.2 Classification -- 6.3 Gaussian Processes with Inducing Variables -- 6.4 Karhunen-Lóeve Expansion -- 6.5 Functional Data Analysis -- Appendix -- Exercises 83sim100 -- Appendix Bibliography.Artificial intelligenceArtificial intelligenceData processingArtificial intelligence.Artificial intelligenceData processing.515.9Suzuki Joe846228MiAaPQMiAaPQMiAaPQ996475762603316Kernel Methods for Machine Learning with Math and Python2851093UNISA