An Introduction to Statistical Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Gareth James 作者

Springer

译者

2013-8-12 出版日期

426 页数

USD 79.99 价格

Hardcover

Springer Texts in Statistics 丛书系列

9781461471370 图书编码

An Introduction to Statistical Learning 在线电子书图书标签: 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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An Introduction to Statistical Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

An Introduction to Statistical Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

An Introduction to Statistical Learning 在线电子书用户评价

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相比PRML确实是入门级的，配合网上的课件和视频，讲得很清楚，主要针对supervised machine learning

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写得这么好的教材竟然还不要钱！业界良心啊~ 唯一的缺点是有点啰嗦……

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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。

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写得这么好的教材竟然还不要钱！业界良心啊~ 唯一的缺点是有点啰嗦……

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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.

An Introduction to Statistical Learning 在线电子书著者简介

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.

An Introduction to Statistical Learning 在线电子书图书目录

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

An Introduction to Statistical Learning 在线电子书图书描述

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 在线电子书下载 mobi epub pdf txt 在线电子书下载

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An Introduction to Statistical Learning 在线电子书读后感

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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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Notes of Introduction to Statistical Learning ===================================== ## Statistical Learning - basic concepts - two main reasons to estimate f: prediction and inference - trade-off: complex models may be good for accurate prediction, but it m...

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1，统计学习的入门书，通俗易懂，号称是ESL的入门版，全书没有太多数学推导，适合学工程的人不适合学统计的人读。2，监督学习占了大部分篇幅，我觉得这本书最好的部分就是模型的讨论都围绕variance和bias的trade-off展开，还有就是对模型的整体性能，以及参数的经验取值都给出...

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业界良心，为学渣精心打造……深入浅出，甚至连矩阵怎么算怕你不会都告诉你，而且尽量避免使用矩阵之类的纯数学的表达，比较适合只学习应用的同学，不用关心太多内在证明。例子给的也很足，非常实际。R的例子讲的也很实用。总之非常适合自学。

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

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An Introduction to Statistical Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024