-
Pattern Recognition Ch.1 REF Brief Review of Matrices, Vectors, Probability and Random Variables
-
Pattern Recognition Ch.3-2 REF #1 A Tutorial on Principal Components Analysis, Jonathon Shlens
-
Pattern Recognition Ch.4-1 Non-Parametric Classification - kNN wPkNN
-
Pattern Recognition Ch.3-1 Maximum-Likelihood & Bayesian Parameter Estimation upload
-
Pattern Recognition Ch.1 REF Statistical Pattern Recognition A Review
-
Pattern Recognition Ch.2 BayesianDecisionTheory part 1 and part 2
-
Pattern Recognition Ch.2 BayesianDecisionTheory part 3
-
Pattern Recognition Ch.4-2 Non-Parametric Classification - Non Bayesian Methods - Decision Trees, Ensemble Learning, Boosting, Random Forests
-
Pattern Recognition Ch.3-2 Component Analysis and Discriminants upload
-
Pattern Recognition Ch.0 syllabus 113-1 ENG
-
Pattern Recognition Ch.1 REF Introduction to Probability
-
Pattern Recognition Ch.1 PR Applications upload
