Tutorials on Machine Learning and Artifical Intelligence

This is a tutorial page for the CPAMI web site. It is created mostly by researchers of CPAMI. It covers various areas of Machine Learning, Artificial Intelligence, Computational Intelligence. It will be updated regularly to cover as many of the areas of CPAMI as possible.

• Hidden Markov Model: Tutorial
• Multi-dimensional Scaling, Sammon Mapping and Isomap: Tutorial
• Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial
• Sampling Algorithms, from Survey Sampling to Monte Carlo Methods: Tutorial
• Fitting A Mixture Distribution to Data: Tutorial
• Eigenvalue and Generalized Eigenvalue Problems: Tutorial
• Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
• The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial
• Linear and Quadratic Discriminant Analysis: Tutorial
• Unsupervised and Supervised Principal Component Analysis: Tutorial
• Fisher and Kernel Fisher Discriminant Analysis: Tutorial