Probability for Statistics and Machine Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Probability for Statistics and Machine Learning

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Anirban DasGupta 作者
Springer
譯者
2011-5-1 出版日期
801 頁數
USD 99.00 價格
Hardcover
Springer Texts in Statistics 叢書系列
9781441996336 圖書編碼

Probability for Statistics and Machine Learning 在線電子書 圖書標籤: 機器學習  概率  統計  統計學  概率統計  Statistics  ML  計算機科學   


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發表於2024-12-26

Probability for Statistics and Machine Learning 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Probability for Statistics and Machine Learning 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Probability for Statistics and Machine Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Probability for Statistics and Machine Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Probability for Statistics and Machine Learning 在線電子書 圖書描述

This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.

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