Machine Learning pdf epub mobi txt 电子书下载 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

图书标签: 机器学习 MachineLearning 数据挖掘计算机计算机科学概率统计人工智能

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发表于2025-01-22

Machine Learning epub 下载 mobi 下载 pdf 下载 txt 电子书下载 2025

Machine Learning pdf epub mobi txt 电子书下载 2025

图书描述

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 下载 mobi epub pdf txt 电子书

著者简介

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

图书目录

Machine Learning pdf epub mobi txt 电子书下载

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用户评价

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看的时候不会写代码。可视化做的异常好。

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CSCI 567 Machine Learning 教材。

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这本书优点就是很全面，千余页的大部头，啥都有。缺点也是很全面，每一个点都不太细致，还需要自己去找论文看。

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经典教材

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感觉有点泛泛

读后感

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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。 ==========================================================================================================================================================

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-----------------------------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...

评分☆☆☆☆☆

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...

评分☆☆☆☆☆

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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这本书的作者试图把机器学习进行全景式地展现，根据我有限的机器学习知识，作者把机器学习该有的都涵盖了。这样做一个非常大的缺陷就是东西太多，讲的不够深入，许多例子都是非常笼统，没有做详细解释，就给了一个图，随便说了几句，对于一个初学者，怎么可能理解的了。书中...

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Machine Learning pdf epub mobi txt 电子书下载 2025