03148nam 2200505 450 99646442740331620220419114908.0981-15-7877-X10.1007/978-981-15-7877-9(CKB)4100000011994899(DE-He213)978-981-15-7877-9(MiAaPQ)EBC6689292(Au-PeEL)EBL6689292(OCoLC)1263026447(PPN)257354824(EXLCZ)99410000001199489920220419d2021 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierStatistical learning with math and python 100 exercises for building logic /Joe Suzuki1st ed. 2021.Singapore :Springer,[2021]©20211 online resource (XI, 256 p. 446 illus., 170 illus. in color.) 981-15-7876-1 Chapter 1: Linear Algebra -- Chapter 2: Linear Regression -- Chapter 3: Classification -- Chapter 4: Resampling -- Chapter 5: Information Criteria -- Chapter 6: Regularization -- Chapter 7: Nonlinear Regression -- Chapter 8: Decision Trees -- Chapter 9: Support Vector Machine -- Chapter 10: Unsupervised Learning.The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building Python programs. As the preliminary part, Chapter 1 provides a concise introduction to linear algebra, which will help novices read further to the following main chapters. Those succeeding chapters present essential topics in statistical learning: linear regression, classification, resampling, information criteria, regularization, nonlinear regression, decision trees, support vector machines, and unsupervised learning. Each chapter mathematically formulates and solves machine learning problems and builds the programs. The body of a chapter is accompanied by proofs and programs in an appendix, with exercises at the end of the chapter. Because the book is carefully organized to provide the solutions to the exercises in each chapter, readers can solve the total of 100 exercises by simply following the contents of each chapter. This textbook is suitable for an undergraduate or graduate course consisting of about 12 lectures. Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning.Mathematical statisticsLogic, Symbolic and mathematicalPython (Computer program language)Mathematical statistics.Logic, Symbolic and mathematical.Python (Computer program language)519.5Suzuki Joe846228MiAaPQMiAaPQMiAaPQBOOK996464427403316Statistical Learning with Math and Python1890233UNISA