An Introduction to Statistical Learning pdf epub mobi txt 电子书下载 2025

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Gareth James

Springer

2013-8-12

426

USD 79.99

Hardcover

Springer Texts in Statistics

9781461471370

图书标签: 机器学习统计学习 R 统计数据分析 Statistics 统计学 machine_learning

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发表于2025-03-04

An Introduction to Statistical Learning epub 下载 mobi 下载 pdf 下载 txt 电子书下载 2025

An Introduction to Statistical Learning pdf epub mobi txt 电子书下载 2025

图书描述

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. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

An Introduction to Statistical Learning 下载 mobi epub pdf txt 电子书

著者简介

Gareth James is a professor of data sciences and operations at the University of Southern California. He has published an extensive body of methodological work in the domain of statistical learning with particular emphasis on high-dimensional and functional data. The conceptual framework for this book grew out of his MBA elective courses in this area.

Daniela Witten is an associate professor of statistics and biostatistics at the University of Washington. Her research focuses largely on statistical machine learning in the high-dimensional setting, with an emphasis on unsupervised learning.

Trevor Hastie and Robert Tibshirani are professors of statistics at Stanford University, and are co-authors of the successful textbook Elements of Statistical Learning. Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap.

图书目录

An Introduction to Statistical Learning pdf epub mobi txt 电子书下载

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用户评价

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applied regression analysis课的textbook，结果prof就直接拿着stanford learning上两个作者公开课的 slide直接用了。。挺适合自学的

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好书！另此书又名“给学渣的机器学习书”。。。。

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Very well written practical overview on statistical pattern recognition. Stay true to the spirit of outlining the essence and not let the mathematical technicalities clutter up discussions. Key themes such as bias-variance trade-off are coherently emphasized throughout. An extremely enjoyable read.

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拯救看不懂ESL的学渣们所写的一本书，作者着实佛心

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还有什么好说呢？豆瓣评分9.5分，多少书有这么高的评价呢？超级易懂，超级有用，我甚至建议所有大学生都读一遍，不论专业……当然了，这是入门基础内容，其作用是又快又好的把基本功打扎实，而高深的东西还需要研读其它好书。

读后感

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http://www-bcf.usc.edu/~gareth/ISL/ ==========================================================================================================================================================

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1. expected test MSE use：to assess the accuracy of model predictions. obtain: repeatedly estimate f using a large number of training sets and test each at x0. decompose: into 3 parts -- variance, bias and irreducible error. note: the meaning of variance an...

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http://www-bcf.usc.edu/~gareth/ISL/ ==========================================================================================================================================================

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这本书读起来不费劲，弱化了数学推导过程，注重思维的直观理解和启发。读起来很畅快，个人感觉第三章线性回归写的很好，即使是很简单的线性模型，作者提出的几个问题和细细的解释这些问题对人很有启发性，逻辑梳理得很好，也易懂。(不过有点可惜的是翻译版本确实不是太好，有些...

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An Introduction to Statistical Learning pdf epub mobi txt 电子书下载 2025