Probability for Statistics and Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

☆☆☆☆☆
简体网页||繁体网页

Anirban DasGupta 作者

Springer

译者

2011-5-1 出版日期

801 页数

USD 99.00 价格

Hardcover

Springer Texts in Statistics 丛书系列

9781441996336 图书编码

Probability for Statistics and Machine Learning 在线电子书图书标签: 机器学习概率统计统计学概率统计 Statistics ML 计算机科学

喜欢 Probability for Statistics and Machine Learning 在线电子书的读者还喜欢

下载链接在页面底部

点击这里下载

想要找书就要到图书目录大全

book.wenda123.org

立刻按 ctrl+D收藏本页

你会得到大惊喜!!

发表于2024-06-27

facebook linkedin mastodon messenger pinterest reddit telegram twitter viber vkontakte whatsapp 复制链接

Probability for Statistics and Machine Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Probability for Statistics and Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Probability for Statistics and Machine Learning 在线电子书用户评价

评分☆☆☆☆☆

Probability for Statistics and Machine Learning 在线电子书著者简介

Probability for Statistics and Machine Learning 在线电子书图书目录

Probability for Statistics and Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Probability for Statistics and Machine Learning 在线电子书图书描述

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.

Probability for Statistics and Machine Learning 在线电子书下载 mobi epub pdf txt 在线电子书下载

想要找书就要到图书目录大全

book.wenda123.org

立刻按 ctrl+D收藏本页

你会得到大惊喜!!