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2025-05-26

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

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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。

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:無

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感覺有點泛泛

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感覺有點泛泛

讀後感

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纯搬运。来自：https://www.cs.ubc.ca/~murphyk/MLbook/errata.html 提交新的bug fix：https://docs.google.com/forms/d/e/1FAIpQLSdOXvmnvuIQn__t0xPyTErj53L-qo_RerImgKbXV4VfLDI6SQ/viewform?formkey=dEp2U2hRWXVpMU5nd05YcEJKVFNUdmc6MQ - preface: added printing hi...

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☆☆☆☆☆

-----------------------------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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哥们就是一个苦逼的本科小民工啊，在ml上完全没有受到过系统的学习，从大约1年半前开始接触机器学习至今，总共看过AG的video，看过《机器学习》和《模式分类》，后来又看了李航的《统计学习方法》，啃过《prml》，学到的东西总感觉零零散散，由于远离ml的圈子，缺乏对这个领域...

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另外的两本分别是PRML和ESLII。这本书的成书时间最晚，刚出的时候特意花了90刀从亚马逊买的。先说说优点：新，全！刚说了，相对于另外两本书，由于成书时间较晚，所以涵盖了更多最近几年的hot topic，比如Dirichlet Process，在其他另外两本书中都没有提到过。更重要的，是...

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Machine Learning pdf epub mobi txt 電子書下載 2025