Introduction to Machine Learning

All slides

• Introduction
• Feature selection
• Feature selection algorithms and some generative models
• Nonparameteric density estimation and Bayesian inference
• Regression
• Classification
• Learning techniques
• Clustering

• Masashi Sugiyama. Introduction to Statistical Machine Learning. Morgan Kaufmann, 2015.
• Isabelle Guyon, Steve Gunn, Masoud Nikravesh, and Lofti A. Zadeh (Eds.). Feature Extraction: Foundations and Applications. Springer-Verlag Berlin Heidelberg, 2006.
• Samuel J. Gershmana and David M. Blei. A Tutorial on Bayesian Nonparametric Models. arXiv:1106.2697v2 [stat.ML], 2011.
• Charles Sutton and Andrew McCallum. "An Introduction to Conditional Random Fields", Foundations and Trends in Machine Learning. (4):4 2012, 267-373
• Leonard Kaufman and Peter J. Rousseeuw. Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, 2005.
• Rui Xu and Donald Wunsch II. "Survey of Clustering Algorithms", IEEE Transactions on Neural Networks. (16):3 May 2005, 645 – 678.