{"title":"Machine Learning Books","description":null,"products":[{"product_id":"an-introduction-to-statistical-learning-with-applications-in-r-springer-texts-in-statistics","title":"An Introduction to Statistical Learning: With Applications in R, Second Edition – Gareth James, Daniela Witten, Trevor Hastie \u0026 Robert Tibshirani (Paperback)","description":"\u003cp\u003e\u003cstrong\u003e\u003cspan\u003eAn Introduction to Statistical Learning: With Applications in R, Second Edition\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e by \u003c\/span\u003e\u003cstrong\u003e\u003cspan\u003eGareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani\u003c\/span\u003e\u003c\/strong\u003e\u003cspan\u003e provides an accessible introduction to statistical learning methods used to analyze data, understand relationships, and develop predictive models.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eDesigned for statisticians and non-statisticians alike, this textbook explains important statistical learning techniques with an emphasis on practical applications. It uses clear explanations, color illustrations, and real-world examples to make complex concepts easier to understand. Each chapter includes an R tutorial that demonstrates how the methods can be implemented using the open-source R statistical computing environment.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThe book covers a broad range of techniques, including regression, classification, resampling, model selection, regularization, tree-based methods, support vector machines, deep learning, survival analysis, unsupervised learning, and multiple testing.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003e\u003cspan\u003eWhat's New in the Second Edition?\u003c\/span\u003e\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eNew chapters on deep learning, survival analysis, and multiple testing\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eExpanded coverage of naïve Bayes\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eExpanded discussion of generalized linear models\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eAdditional material on Bayesian additive regression trees\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eExpanded treatment of matrix completion\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eUpdated R code throughout for improved compatibility\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eNew examples and applications supporting the study of statistical learning\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003e\u003cspan\u003eKey Topics Covered\u003c\/span\u003e\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eStatistical learning fundamentals\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eLinear regression and classification\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eResampling methods\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eLinear model selection and regularization\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eMoving beyond linearity\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eTree-based methods\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eSupport vector machines\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eDeep learning\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eSurvival analysis\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eUnsupervised learning and clustering\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003eMultiple testing\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cspan\u003ePractical statistical modeling and prediction\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003e\u003cspan\u003eLearn Through Practical R Tutorials\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cspan\u003eEach chapter includes a laboratory section that demonstrates how to apply the methods covered in the text using R. These tutorials help readers connect statistical concepts with practical data analysis and develop familiarity with commonly used statistical learning techniques.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThe book assumes a previous course in linear regression and does not require prior knowledge of matrix algebra, making it suitable for readers seeking an approachable introduction to the subject.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003e\u003cspan\u003eIdeal For\u003c\/span\u003e\u003c\/h2\u003e\n\u003cp\u003e\u003cspan\u003eStatistics and data science students, researchers, analysts, scientists, business professionals, and practitioners interested in statistical modeling, data analysis, machine learning, and predictive methods.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003e\u003cspan\u003eProduct Details\u003c\/span\u003e\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth\u003e\u003cspan\u003eDetail\u003c\/span\u003e\u003c\/th\u003e\n\u003cth\u003e\u003cspan\u003eInformation\u003c\/span\u003e\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eBook Title\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eAn Introduction to Statistical Learning\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eSubtitle\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eWith Applications in R\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eAuthors\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eGareth James; Daniela Witten; Trevor Hastie; Robert Tibshirani\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003ePublisher\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eSpringer\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eSeries\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eSpringer Texts in Statistics\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eEdition\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eSecond Edition (2021)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003ePaperback Publication Date\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eJuly 30, 2022\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eISBN-13\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003e9781071614204\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eISBN-10\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003e1071614207\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eBinding\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003ePaperback\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eLanguage\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eEnglish\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eNumber of Pages\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003e607 numbered pages (plus XV preliminary pages)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eProduct Condition\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003eNew\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cspan\u003eFormat\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan\u003ePhysical Paperback Book\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"thebookscharm.com","offers":[{"title":"Default Title","offer_id":67233213513977,"sku":"ISL2R-9781071614204","price":34.97,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0840\/6948\/2745\/files\/AnIntroductiontoStatisticalLearningwithApplicationsinR.jpg?v=1790552260"},{"product_id":"reinforcement-learning","title":"Reinforcement Learning: An Introduction, 2nd Edition – Richard S. 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