Machine Learning 2025 pdf epub mobi 电子书

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Machine Learning 2025 pdf epub mobi 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.

Machine Learning 电子书图书目录

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发表于2025-04-11

Machine Learning 2025 pdf epub mobi 电子书

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Machine Learning 电子书读后感

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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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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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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...

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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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出版者:The MIT Press

作者:Kevin P·Murphy

出品人:

页数:1096

译者:

出版时间:2012-9-18

价格:USD 90.00

装帧:Hardcover

isbn号码:9780262018029

丛书系列:Adaptive Computation and Machine Learning

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

Machine Learning 2025 pdf epub mobi 电子书图书描述

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 2025 pdf epub mobi 电子书

想要找书就要到本本书屋

onlinetoolsland.com

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