Machine Learning pdf epub mobi txt 電子書下載 2025

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Kevin P·Murphy

The MIT Press

2012-9-18

1096

USD 90.00

Hardcover

Adaptive Computation and Machine Learning

9780262018029

圖書標籤: 機器學習 MachineLearning 數據挖掘計算機計算機科學概率統計人工智能

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发表于2025-01-10

Machine Learning epub 下載 mobi 下載 pdf 下載 txt 電子書下載 2025

Machine Learning pdf epub mobi txt 電子書下載 2025

圖書描述

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Machine Learning 下載 mobi epub pdf txt 電子書

著者簡介

Kevin P. Murphy is Associate Professor in the Department of Computer Science and in the Department of Statistics at the University of British Columbia.

圖書目錄

Machine 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

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立刻按 ctrl+D收藏本頁

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用戶評價

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Chapter 1-3, 07.09.2019; C4 (Gaussian models) 07.12; C5 (Bayesian statistics) 07.19;C6 (Frequentist statistics) 07.20; C7 (Linear regression) 07.29; C8 (Logistic regression) 08.22

評分☆☆☆☆☆

不夠係統，有點亂，小錯有點多。瑕不掩瑜，仍是經典。Machine Learning就兩本書，PRML和這本。

評分☆☆☆☆☆

內容較新及全麵。

評分☆☆☆☆☆

剛剛翻自己mark過的讀過的書，發現18-19年的讀書痕跡有點淡。大概因為很多時間花在讀課本讀雜誌上麵瞭。

讀後感

評分☆☆☆☆☆

为什么评分这么高?谁学过，谁学完了？为什么评分这么高?谁学过，谁学完了？为什么评分这么高?谁学过，谁学完了？为什么评分这么高?谁学过，谁学完了？为什么评分这么高?谁学过，谁学完了？为什么评分这么高?谁学过，谁学完了？为什么评分这么高?谁学过，谁学完了？为什么评分这...

評分☆☆☆☆☆

断断续续读了本书几章内容，并扫了一眼全书，个人感觉这本书就是一本大杂烩。这本书涉及的内容很广，概率图模型、GLM、Nonparametric Method，甚至最近比较火的Deep Learning也包括了。但是，感觉很多地方讲的不是很细致，每每读到关键地方，都有种嘎然而止的感觉。不过还好...

評分☆☆☆☆☆

判别模型几乎没怎么讲。。后面各种生成模型，贝叶斯网、随机场、MCMC、HMM。 ==========================================================================================================================================================

評分☆☆☆☆☆

-----------------------------读完第三章更新------------------------------ 啪啪啪啪啪啪啪啪啪啪啪，先自扇十个大耳光。这本书还是不错的，很深，我写了个第三章的笔记，欢迎拍砖。http://book.douban.com/annotation/23203104/ 第三章可读性比第二章好得多，但是说实话还...

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Awesome! 1. 与这本书的缘分竟始于化学系图书馆(没有其它两本，PRML or the Elements，也许因为K Murphy是校友的缘故。。不过C Bishop就在附近的Microsoft啊) 最终在黑五我还是买了这本书，装帧结实漂亮；留白够多，这样可以随意增添喜欢的内容和推导。英Amazon比较厚道，便宜...

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Machine Learning pdf epub mobi txt 電子書下載 2025