Difference between revisions of "Resources"

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* [http://eaai.stanford.edu Educational Advances in AI (EAAI)]
 
* [http://eaai.stanford.edu Educational Advances in AI (EAAI)]
 
* [http://modelai.gettysburg.edu Model AI Assignments]
 
* [http://modelai.gettysburg.edu Model AI Assignments]
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=General=
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* Texts:
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** [http://dl.acm.org/citation.cfm?id=1671238 Stuart Russell, Peter Norvig. Artificial Intelligence: a modern approach]
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=Machine Learning=
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* Texts:
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** [http://dl.acm.org/citation.cfm?id=1162264 Christopher Bishop. Pattern Recognition and Machine Learning]
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** [http://dl.acm.org/citation.cfm?id=2380985 Kevin Murphy. Machine Learning: A Probabilistic Perspective]
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** [http://dl.acm.org/citation.cfm?id=2207809 David Barber. Probabilistic Reasoning and Machine Learning] ([http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf Barber's free PDF version])
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** [http://dl.acm.org/citation.cfm?id=541177 Tom Mitchell. Machine Learning]
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** [http://dl.acm.org/citation.cfm?id=1734076 Ethem Alpaydin. Introduction to Machine Learning]
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** Statistical Learning:
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*** [https://statweb.stanford.edu/~tibs/ElemStatLearn/ Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The Elements of Statistical Learning]
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*** [http://www-bcf.usc.edu/~gareth/ISL/ Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. An Introduction to Statistical Learning with Applications in R] ([https://www.rstudio.com/products/rstudio/ RStudio software for labs])
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** Reinforcement Learning:
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*** [http://incompleteideas.net/sutton/book/the-book.html Richard Sutton and Andrew Barto. Reinforcement Learning: an introduction]
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*** [https://sites.ualberta.ca/~szepesva/RLBook.html Csaba Szepesvári. Algorithms for Reinforcement Learning]
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*** [http://dl.acm.org/citation.cfm?id=2670001 Marco Wiering and Martijn van Otterlo. Reinforcement Learning: State-of-the-Art]
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* Online resources:
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** [https://www.coursera.org/learn/machine-learning Andrew Ng's free online Coursera Machine Learning course]
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** [http://archive.ics.uci.edu/ml/ UC Irvine Machine Learning Repository]
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** [https://www.kaggle.com/datasets Kaggle datasets]
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** [https://www.rstudio.com/products/rstudio/ RStudio software for labs]
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** [http://www.cs.waikato.ac.nz/ml/weka/ Weka Java-based Data Mining software] and [http://dl.acm.org/citation.cfm?id=1205860 Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques]
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** [http://modelai.gettysburg.edu/ Model AI Assignments]
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* Recommendations:
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** [https://www.quora.com/How-do-I-learn-machine-learning-1 Quora "How do I learn machine learning?" answers]
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** [https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md Joseph Misiti's Machine Learning book recommendations]

Revision as of 11:07, 1 April 2017

Starting Places

General

Machine Learning

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