模式识别与机器学习

Hacker News 上怎么说

• Yadi · 2018 年

  在机器学习领域，毫无疑问这几本是最顶的相关教材：- [0] Pattern Recognition and Machine Learning (Information Science and Statistics)，还有：- [1] The Elements of Statistical Learning - [2] Reinforcement Learning: An Introduction（Barto 和 Sutton 著）- [3] Deep Learning（Aaron Courville、Ian Goodfellow 和 Yoshua Bengio 著）…

  In machine learning, hands down these are some of the best related textbooks: - [0] Pattern Recognition and Machine Learning (Information Science and Statistics) and also: - [1] The Elements of Statistical Learning - [2] Reinforcement Learning: An Introduction by Barto and Sutton - [3] The Deep Learning by Aaron Courville, Ian Goodfellow, and Yoshua Bengio…

• boltzmannbrain · 2018 年

  > 啃教材。做习题。把它当成学术研究来对待。太赞同了。强烈推荐 Russel & Norvig [1]，用来建立高层次直觉和研究动机。然后用 Bishop 的《Pattern Recognition and Machine Learning》[2] 和 Koller 的 PGM 书 [3] 来打牢基础。别看 MOOC，不过有些公开课视频还是挺管用的，比如 Hugo Larochelle 讲 belief propagation（置信度传播）[4]。顺带提一句（FWIW），这建议来自一个机械工程师……

  > study textbooks. Do exercises. Treat it like academic studying This. Highly recommend Russel & Norvig [1] for high-level intuition and motivation. Then Bishop's "Pattern Recognition and Machine Learning" [2] and Koller's PGM book [3] for the fundamentals. Avoid MOOCs, but there are useful lecture videos, e.g. Hugo Larochelle on belief propagation [4]. FWIW this is coming from a mechanical engineer…

• maurits · 2014 年

  ……网上能找到。http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... Abu-Mostafa 写的《Learning from data》，配套有加州理工的视频公开课：http://work.caltech.edu/telecourse.html。Bischop 写的《Pattern Recognition and Machine Learning》http://research.microsoft.com/en-us/um/people/cmbishop/prml/。另外值得一提的还有 Mackay 的《Information Theory, Inference, and Learning Algorithms》，免费的。http://www.inference.phy.cam.ac.uk/itprnn/book.html…

  …available online. http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... Learning from data, by Abu-Mostafa. It comes with Caltech video lectures: http://work.caltech.edu/telecourse.html Pattern Recognition and Machine Learning, by Bischop http://research.microsoft.com/en-us/um/people/cmbishop/prml/ Also noteworthy Information Theory, Inference, and Learning Algorithms, by Mackay, free. http://www.inference.phy.cam.ac.uk/itprnn/book.html…

• shogunmike · 2015 年

  ……Data (Flach): http://www.amazon.com/Machine-Learning-Science-Algorithms-Se... Machine Learning: A Probabilistic Perspective (Murphy): http://www.amazon.com/Machine-Learning-Probabilistic-Perspec... Pattern Recognition and Machine Learning (Bishop): http://www.amazon.com/Pattern-Recognition-Learning-Informati... 有不少关于贝叶斯统计和图模型（graphical models）的优质资源/好书。我大致按照……的顺序列出来了

  …Data (Flach): http://www.amazon.com/Machine-Learning-Science-Algorithms-Se... Machine Learning: A Probabilistic Perspective (Murphy): http://www.amazon.com/Machine-Learning-Probabilistic-Perspec... Pattern Recognition and Machine Learning (Bishop): http://www.amazon.com/Pattern-Recognition-Learning-Informati... There are some great resources/books for Bayesian statistics and graphical models. I've listed them in (approximate) order of…

• laichzeit0 · 2018 年

  你为什么说我们不明白这些系统是怎么工作的？比如说，随机梯度下降并不是特别神秘。如果你想理解机器学习算法的工作原理和原因，Christopher Bishop 的《Pattern Recognition and Machine Learning》是个很好的起点。

  Why would you say we don't understand how these systems work? Stochastic gradient descent, for example, is not particularly enigmatic. Pattern Recognition and Machine Learning by Christopher Bishop is a good place to start if you want to gain an understanding of how and why machine learning algorithms work.

• adamnemecek · 2016 年

  ……Learning (https://smile.amazon.com/Python-Machine-Learning-Sebastian-R...) * An Introduction to Statistical Learning (https://smile.amazon.com/Introduction-Statistical-Learning-A...) 进阶：* Pattern Recognition and Machine Learning (https://smile.amazon.com/Pattern-Recognition-Learning-Inform...) * Machine Learning: A Probabilistic Perspective (https://smile.amazon.com/Machine-Learning-Probabilistic-Pers...) * All of Statistics:…

  …Learning (https://smile.amazon.com/Python-Machine-Learning-Sebastian-R...) * An Introduction to Statistical Learning (https://smile.amazon.com/Introduction-Statistical-Learning-A...) Intermediate: * Pattern Recognition and Machine Learning (https://smile.amazon.com/Pattern-Recognition-Learning-Inform...) * Machine Learning: A Probabilistic Perspective (https://smile.amazon.com/Machine-Learning-Probabilistic-Pers...) * All of Statistics:…

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