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Deep Learning (Adaptive Computation and Machine Learning series) Ian Goodfellow. 13.1 Introduction 613 13.2 TheF TestforaRandomizedBlockDesign 614 13.3 ThePairedt Test 628 13.4 TakingaSecondLookatStatistics(ChoosingbetweenaTwo-Samplet Test andaPairedt Test) 634 14 NonparametricStatistics 638 14.1 Introduction 638 14.2 TheSignTest 639 14.3 WilcoxonTests 645 14.4 An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. 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In-depth treatment of sufficiency and testing theory includes uniformly most powerful tests and likelihood ratio tests. Errata & data. The material in chapters 19, 24, 25 and 28 is more advanced, with the remaining . Statistics: Learning from Data 2nd Edition by Roxy Peck. Machine learning is rapidly becoming a skill that computer science students must master before graduation. An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. as well as reading Hastie & T.'s "introduction to statistical learning" (which also has free videos available . Introduction to Mathematical Statistics and Its . 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