Back To The Course Mod-01 Lec-01 Introduction to Statistical Pattern Recognition Free Video Tutorials and Notes Lectures Mod-01 Lec-02 Overview of Pattern Classifiers Free Video Tutorials and Notes Lectures Mod-02 Lec-03 The Bayes Classifier for minimizing Risk Free Video Tutorials and Notes Lectures Mod-02 Lec-04 Estimating Bayes Error; Minimax and Neymann-Pearson classifiers Free Video Tutorials and Notes Lectures Mod-03 Lec-05 Implementing Bayes Classifier; Estimation of Class Conditional Densities Free Video Tutorials and Notes Lectures Mod-03 Lec-06 Maximum Likelihood estimation of different densities Free Video Tutorials and Notes Lectures Mod-06 Lec-17 Fisher Linear Discriminant Free Video Tutorials and Notes Lectures Mod-07 Lec-21 Consistency of Empirical Risk Minimization Free Video Tutorials and Notes Lectures Mod-08 Lec-25 Overview of Artificial Neural Networks Free Video Tutorials and Notes Lectures Mod-03 Lec-07 Bayesian estimation of parameters of density functions, MAP estimates Free Video Tutorials and Notes Lectures Mod-03 Lec-08 Bayesian Estimation examples; the exponential family of densities and ML estimates Free Video Tutorials and Notes Lectures Mod-03 Lec-09 Sufficient Statistics; Recursive formulation of ML and Bayesian estimates Free Video Tutorials and Notes Lectures Mod-04 Lec-10 Mixture Densities, ML estimation and EM algorithm Free Video Tutorials and Notes Lectures Mod-04 & 05 Lec-11 Convergence of EM algorithm; overview of Nonparametric density estimation Free Video Tutorials and Notes Lectures Mod-05 Lec-12 Nonparametric estimation, Parzen Windows, nearest neighbour methods Free Video Tutorials and Notes Lectures Mod-06 Lec-13 Linear Discriminant Functions; Perceptron -- Learning Algorithm and convergence proof Free Video Tutorials and Notes Lectures Mod-06 Lec-14 Linear Least Squares Regression; LMS algorithm Free Video Tutorials and Notes Lectures Mod-06 Lec-15 AdaLinE and LMS algorithm; General nonliner least-squares regression Free Video Tutorials and Notes Lectures Mod-06 Lec-16 Logistic Regression; Statistics of least squares method; Regularized Least Squares Free Video Tutorials and Notes Lectures Mod-06 Lec-18 Linear Discriminant functions for multi-class case; multi-class logistic regression Free Video Tutorials and Notes Lectures Mod-07 Lec-19 Learning and Generalization; PAC learning framework Free Video Tutorials and Notes Lectures Mod-07 Lec-20 Overview of Statistical Learning Theory; Empirical Risk Minimization Free Video Tutorials and Notes Lectures Mod-07 Lec-22 Consistency of Empirical Risk Minimization; VC-Dimension Free Video Tutorials and Notes Lectures Mod-07 Lec-23 Complexity of Learning problems and VC-Dimension Free Video Tutorials and Notes Lectures Mod-07 Lec-24 VC-Dimension Examples; VC-Dimension of hyperplanes Free Video Tutorials and Notes Lectures Electronics - Pattern Recognition Free Video Tutorials and Notes LecturesMod-06 Lec-17 Fisher Linear Discriminant Free Video Tutorials and Notes LecturesPattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more details on NPTEL visit http://nptel.ac.in