Machine Learning

[Research Methods]

Lecturer: Dell Zhang
Programme: MPhil and PhD
Date/Time: Wednesday 8 Nov 2017, 8pm - 9pm
Room: MAL 151 [BBK Maps]


Machine Learning: To Be or Not To Be

Machine Learning Software

Python for Machine Learning

Java for Machine Learning

Machine Learning Datasets

UCI Machine Learning Repository


Eric Mjolsness and Dennis DeCoste, Machine Learning for Science: State of the Art and Future Prospect, Science, Vol. 293. no. 5537, pp. 2051-2055, 14 September 2001.
Peter Norvig: Statistical Learning as the Ultimate Agile Development Tool, CIKM, Oct 2008.
Andrew Ng: Advice on Applying Machine Learning.
Pedro Domingos: A Few Useful Things to Know about Machine Learning, CACM, Oct 2012.

Paul Graham: A Plan for Spam.
Paul Graham: Better Bayesian Filtering.
Robert M. Bell et al.: The Million Dollar Programming Prize, IEEE Spectrum, May 2009.

Toby Segaran, Programming Collective Intelligence: Building Smart Web 2.0 Applications, O'Reilly, 2007.
Matthew Russell, Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites, O'Reilly, 2011.
Satnam Alag, Collective Intelligence in Action , Manning, 2008.
Haralambos Marmanis and Dmitry Babenko, Algorithms of the Intelligent Web , Manning, 2009.

Ron Zacharski, A Programmer's Guide to Data Mining, Free Online eBook.

Hans Rosling: The Joy of Stats [Video].

Further Readings

Tom Mitchell, Machine Learning, McGraw Hill, 1997. (Chapter 1)
Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd edition, Prentice Hall, 2010. (Part V: Learning)

Kevin Murphy, Machine Learning: A Probabilistic Perspective, MIT Press, 2012. (Chapter 1)
Stephen Marsland, Machine Learning: An Algorithmic Perspective, Chapman & Hall/CRC, 2009.
Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006. (Chapter 1)
Richard Duda, Peter Hart, and David Stork, Pattern Classification, 2nd edition, Wiley-Blackwell, 2000. (Chapter 1)
Anand Rajaraman and Jeff Ullman, Mining of Massive Datasets. (Chapter 1)
Ian H. Witten, Eibe Frank, and Mark A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 3rd Ed., Morgan Kaufmann, 2011. (Chapter 1)

AAAI, AI Topic: Machine Learning (Good Places to Start).
Nils J. Nilsson, Introduction to Machine Learning, Draft of Incomplete Notes. (Chapter 1)
Andrew Moore, Statistical Data Mining Tutorials
David MacKay, Information Theory, Inference, and Learning Algorithms , Cambridge University Press, 2003. (Free Online)


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