An Introduction to Statistical Learning pdf epub mobi txt 電子書 下載 2024


An Introduction to Statistical Learning

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Gareth James
Springer
2013-8-12
426
USD 79.99
Hardcover
Springer Texts in Statistics
9781461471370

圖書標籤: 機器學習  統計學習  R  統計  數據分析  Statistics  統計學  machine_learning   


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发表于2024-12-22

An Introduction to Statistical Learning epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

An Introduction to Statistical Learning epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

An Introduction to Statistical Learning pdf epub mobi txt 電子書 下載 2024



圖書描述

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 下載 mobi epub pdf txt 電子書

著者簡介

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.


圖書目錄


An Introduction to Statistical Learning pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

用戶評價

評分

寫的的確非常簡明易懂。讀過以後給瞭我“已經懂瞭ML”的幻覺。還是老老實實讀Elements那本去吧

評分

理論解釋非常到位,但需要結閤code與case study來消化吸收,應用

評分

好書!另此書又名“給學渣的機器學習書”。。。。

評分

簡明清晰,對於常用的方法基本都有涉獵。對讀者的知識背景沒太多要求,所以也很難深入。差不多是當成復習+加深印象。本來是想讀elements那本,可是綫性代數忘光瞭,看著矩陣證明真想以頭搶地T-T

評分

ISLR在機器學習界大名鼎鼎,個人認為是最適閤初級學習者的著作。雖說是ESLR的簡化版,但是精華該有的都有,全書脈絡清晰無比,從Bias-Variance Tradeoff和No Free Lunch兩條基本思想展開,作者的深厚統計學背景使得LogReg、PCA和LDA這些概念主題都能有一個清楚的闡釋。以理論為主,但是也有lab,方便讀者動手一窺究竟。這本書甚至激起瞭我的一點學習數學的心情,接下來打算用Strang的那本綫代和Casella的統計推斷好好鞏固基礎,屆時再迴味想必又能有新的體會。Logistic和SVM等部分讀起來一氣嗬成,真可謂“清水齣芙蓉”,而對模型的討論始終堅持問題導嚮,有一些哲學思維。唯一的遺憾就是預期讀者的數學水平掣肘瞭內容的發揮。

讀後感

評分

其实我最大的感触是书中总是说某某内容 “ is beyond the scope of this book” ,真是难为几位作者了。 --------------------------- 高清无码图见相册: https://www.douban.com/photos/photo/2462258822/  

評分

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...  

評分

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...  

評分

其实我最大的感触是书中总是说某某内容 “ is beyond the scope of this book” ,真是难为几位作者了。 --------------------------- 高清无码图见相册: https://www.douban.com/photos/photo/2462258822/  

評分

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

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