An Introduction to Statistical Learning pdf epub mobi txt 電子書下載 2025

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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2025-03-27

An Introduction to Statistical Learning epub 下載 mobi 下載 pdf 下載 txt 電子書下載 2025

An Introduction to Statistical Learning pdf epub mobi txt 電子書下載 2025

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

qciss.net

立刻按 ctrl+D收藏本頁

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用戶評價

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。

評分☆☆☆☆☆

果然是element of statistical learning的R語言簡明版。或者看成ESL的導讀也行。

評分☆☆☆☆☆

是寫的很好，常用的基礎算法裏麵缺瞭神經網絡，不過光看這本也是遠遠不夠的。。。

評分☆☆☆☆☆

終於讀完瞭。沒有用 R ，還是偷懶用瞭 Python 的 scikit learn，基本差不多。

評分☆☆☆☆☆

是寫的很好，常用的基礎算法裏麵缺瞭神經網絡，不過光看這本也是遠遠不夠的。。。

讀後感

評分☆☆☆☆☆

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。

評分☆☆☆☆☆

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...

評分☆☆☆☆☆

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 電子書下載 2025