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2025-02-25

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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:无

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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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不够系统，有点乱，小错有点多。瑕不掩瑜，仍是经典。Machine Learning就两本书，PRML和这本。

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翻了两章果断放下。不懂的人看不懂，懂的人看你干嘛。‘全’是逼格最低的优点。

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内容较新及全面。

读后感

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这是我为本书第四次（我买的是第六次印刷，但是是一样的）印刷写的勘误表：https://github.com/ks838/Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing

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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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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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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...

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Machine Learning pdf epub mobi txt 电子书下载 2025