Machine learning - Revision history

Matthew at 20:14, 11 October 2017

2017-10-11T20:14:00Z

← Older revision		Revision as of 20:14, 11 October 2017
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	* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]		* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]
	* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]		* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]
	* [https://web.stanford.edu/~hastie/Papers/ESLII.pdf Hastie, Tibshirani, and Friedman's book], also [http://www-bcf.usc.edu/~gareth/ISL/ James, Witten, Hastie, and Tibshirani's book] which has less focus on mathematical foundations and more on applications (in R).		* [https://web.stanford.edu/~hastie/Papers/ESLII.pdf Hastie, Tibshirani, and Friedman's book]; also [http://www-bcf.usc.edu/~gareth/ISL/ James, Witten, Hastie, and Tibshirani's book], which has less focus on mathematical foundations and more on applications (in R).

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2017-10-11T20:13:05Z

← Older revision		Revision as of 20:13, 11 October 2017
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	* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]		* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]
	* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]		* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]
	* [https://web.stanford.edu/~hastie/Papers/ESLII.pdf Hastie, Tibshirani, and Friedman's book]		* [https://web.stanford.edu/~hastie/Papers/ESLII.pdf Hastie, Tibshirani, and Friedman's book], also [http://www-bcf.usc.edu/~gareth/ISL/ James, Witten, Hastie, and Tibshirani's book] which has less focus on mathematical foundations and more on applications (in R).

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2017-10-10T13:55:24Z

Online Machine Learning Resources

← Older revision		Revision as of 13:55, 10 October 2017
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	* [http://setosa.io/ev/markov-chains/ Markov Chains explained visually]		* [http://setosa.io/ev/markov-chains/ Markov Chains explained visually]
	* [https://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox Mo Chen's toolbox] for all the methods discussed in the book: Pattern Recognition and Machine Learning by C. Bishop		* [https://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox Mo Chen's toolbox] for all the methods discussed in the book: Pattern Recognition and Machine Learning by C. Bishop
			* [http://www.arxiv-sanity.com arXiv Sanity Preserver], an interface to the machine learning section of arXiv; lists recent papers most discussed in social media, and gives similar paper recommendations.

2017-09-12T16:22:24Z

Machine learning books

← Older revision		Revision as of 16:22, 12 September 2017
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	* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]		* [http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf Harrington's book]
	* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]		* [http://www.deeplearningbook.org/ Ian Goodfellow, Yoshua Bengio, and Aaron Courville's book]
			* [https://web.stanford.edu/~hastie/Papers/ESLII.pdf Hastie, Tibshirani, and Friedman's book]

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2017-07-04T18:31:31Z

← Older revision		Revision as of 18:31, 4 July 2017
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	== Online Machine Learning Resources ==		== Online Machine Learning Resources ==
	* [https://www.coursera.org/learn/machine-learning ML course by Stanford computer scientist Andrew Ng (requires Coursera signup --> free enrollment)]		* [https://www.coursera.org/learn/machine-learning ML course by Stanford computer scientist Andrew Ng (requires Coursera signup --> free enrollment)]
	*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]		* [http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]
	*[http://setosa.io/ev/markov-chains/ Markov Chains explained visually]		* [http://setosa.io/ev/markov-chains/ Markov Chains explained visually]
			* [https://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox Mo Chen's toolbox] for all the methods discussed in the book: Pattern Recognition and Machine Learning by C. Bishop

2016-09-14T17:49:33Z

← Older revision		Revision as of 17:49, 14 September 2016
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	== Online Machine Learning Resources ==		== Online Machine Learning Resources ==
	* [https://www.coursera.org/learn/machine-learning ML ~~online~~ course by Andrew Ng (requires Coursera signup --> free enrollment)]		* [https://www.coursera.org/learn/machine-learning ML course by Stanford computer scientist Andrew Ng (requires Coursera signup --> free enrollment)]
	*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]		*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]
	*[http://setosa.io/ev/markov-chains/ Markov Chains explained visually]		*[http://setosa.io/ev/markov-chains/ Markov Chains explained visually]

2016-09-14T17:48:21Z

Online Machine Learning Resources

← Older revision		Revision as of 17:48, 14 September 2016
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	* [https://www.coursera.org/learn/machine-learning ML online course by Andrew Ng (requires Coursera signup --> free enrollment)]		* [https://www.coursera.org/learn/machine-learning ML online course by Andrew Ng (requires Coursera signup --> free enrollment)]
	*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]		*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]
			*[http://setosa.io/ev/markov-chains/ Markov Chains explained visually]

2016-09-14T17:47:14Z

← Older revision		Revision as of 17:47, 14 September 2016
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			== Online Machine Learning Resources ==
			* [https://www.coursera.org/learn/machine-learning ML online course by Andrew Ng (requires Coursera signup --> free enrollment)]
			*[http://www.johnwittenauer.net/machine-learning-exercises-in-python-part-1/ Andrew Ng ML course exercises for Python]

2016-06-27T19:14:03Z

← Older revision		Revision as of 19:14, 27 June 2016
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	* [[Media:ML-ANNs.pdf \| Rate-based networks & error back-propagation learning]] - Scott		* [[Media:ML-ANNs.pdf \| Rate-based networks & error back-propagation learning]] - Scott
	* [[Media:Support Vector Machines (SVM).pdf \| Support Vector Machines]] - Jerry		* [[Media:Support Vector Machines (SVM).pdf \| Support Vector Machines]] - Jerry
	* Deep belief networks		* [[Media:Deep_Belief_Network_Home_(2).pdf \| Deep belief networks ]] - Tiger

2016-06-21T19:33:56Z

← Older revision		Revision as of 19:33, 21 June 2016
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	* [[Media:Support Vector Machines (SVM).pdf \| Support Vector Machines]] - Jerry		* [[Media:Support Vector Machines (SVM).pdf \| Support Vector Machines]] - Jerry
	* Deep belief networks		* Deep belief networks
	* Supervised vs. unsupervised learning

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