Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: 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. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
發表於2024-12-23
統計學習基礎(第2版)(英文) 2024 pdf epub mobi 電子書 下載
[https://web.stanford.edu/~hastie/ElemStatLearn/] ==========================================================================================================================================================
評分我導師(stanford博士畢業)非常欣賞這本書,並把它作為我博士資格考試的參考教材之一。 感謝 ZHENHUI LI 提供的信息。本書作者已經將第二版的電子書放到網上,大傢可以免費下載。 http://www-stat.stanford.edu/~tibs/ElemStatLearn/ 網上還有一份solution manual, 但是似乎...
評分評論最下麵的部分Version 1是我開始讀這本書的時候寫的東西,現在加上點基礎部分。 對linear algebra, probability 要有非常強的直觀認識,對這兩個基礎學的非常通透。Linear algebra 有幾種常用的分解QR, eigendecomposition, SVD,搞清楚它們的作用和幾何意義。Bayesian meth...
評分 評分douban評論非要給齣評價纔能發錶,這非常難決斷 說你好呢,翻譯的亂七八糟 說你不好呢,內容實在深刻 說起翻譯來,這可是把中文說的比外文還難懂 Jiawei Han的數據挖掘讓範明譯的汙七八糟 結果還讓他來翻譯這部經典,懷疑他在用google翻譯 最後還是忍不住去圖書館復印瞭原版...
圖書標籤: 機器學習 統計學習 統計學 數據挖掘 數學 統計 數據分析 statistics
其實這本書有個姐妹篇,叫 An Introduction to Statistical Learning: with Applications in R ,是Hastie 和Tibshirani 和另外兩個作者閤寫的,更加適閤入門,是非常經典的教材。
評分A comprehensive book concerning ML. I recommend it to advanced readers equipped with extensive solid mathematical foundation, especially certain core courses of statistics(e.g., multivariate statistical analysis), matrix theory, optimization theory and numerical analysis.
評分樓下有幾位兄颱對“基礎”的要求未免太苛刻瞭,這是麵嚮研究生的書籍,應該用評價GTM的標準來衡量它啊。 而且本書的門檻是本科那些知識學紮實就可以讀瞭,做學問來說這難道還不夠基礎麼?
評分哼,說好的基礎呢!!!一點都不基礎,看得我纍死瞭,然後放棄瞭
評分不適閤沒怎麼學過統計和綫性代數的人看,不太友好
統計學習基礎(第2版)(英文) 2024 pdf epub mobi 電子書 下載