Back To The Course Mod-01 Lec-01 Principles of Pattern Recognition I (Introduction and Uses) Free Video Tutorials and Notes Lectures Mod-01 Lec-02 Principles of Pattern Recognition II (Mathematics) Free Video Tutorials and Notes Lectures Mod-01 Lec-03 Principles of Pattern Recognition III (Classification and Bayes Decision Rule) Free Video Tutorials and Notes Lectures Mod-01 Lec-04 Clustering vs. Classification Free Video Tutorials and Notes Lectures Mod-01 Lec-05 Relevant Basics of Linear Algebra, Vector Spaces Free Video Tutorials and Notes Lectures Mod-01 Lec-06 Eigen Value and Eigen Vectors Free Video Tutorials and Notes Lectures Mod-01 Lec-07 Vector Spaces Free Video Tutorials and Notes Lectures Mod-01 Lec-08 Rank of Matrix and SVD Free Video Tutorials and Notes Lectures Mod-02 Lec-09 Types of Errors Free Video Tutorials and Notes Lectures Mod-02 Lec-10 Examples of Bayes Decision Rule Free Video Tutorials and Notes Lectures Mod-02 Lec-11 Normal Distribution and Parameter Estimation Free Video Tutorials and Notes Lectures Mod-02 Lec-12 Training Set, Test Set Free Video Tutorials and Notes Lectures Mod-02 Lec-13 Standardization, Normalization, Clustering and Metric Space Free Video Tutorials and Notes Lectures Mod-02 Lec-14 Normal Distribution and Decision Boundaries I Free Video Tutorials and Notes Lectures Mod-02 Lec-15 Normal Distribution and Decision Boundaries II Free Video Tutorials and Notes Lectures Mod-02 Lec-17 Linear Discriminant Function and Perceptron Free Video Tutorials and Notes Lectures Mod-02 Lec-19 Linear and Non-Linear Decision Boundaries Free Video Tutorials and Notes Lectures Mod-02 Lec-20 K-NN Classifier Free Video Tutorials and Notes Lectures Mod-02 Lec-21 Principal Component Analysis (PCA) Free Video Tutorials and Notes Lectures Mod-02 Lec-22 Fisher’s LDA Free Video Tutorials and Notes Lectures Mod-02 Lec-18 Perceptron Learning and Decision Boundaries Free Video Tutorials and Notes Lectures Mod-02 Lec-23 Gaussian Mixture Model (GMM) Free Video Tutorials and Notes Lectures Mod-02 Lec-24 Assignments Free Video Tutorials and Notes Lectures Mod-03 Lec-25 Basics of Clustering, Similarity/Dissimilarity Measures, Clustering Criteria. Free Video Tutorials and Notes Lectures Mod-03 Lec-26 K-Means Algorithm and Hierarchical Clustering.. Free Video Tutorials and Notes Lectures Computer Science - Pattern Recognition Free Video Tutorials and Notes LecturesMod-01 Lec-07 Vector Spaces Free Video Tutorials and Notes LecturesPattern Recognition by Prof. C.A. Murthy & Prof. Sukhendu Das,Department of Computer Science and Engineering,IIT Madras.For more details on NPTEL visit http://nptel.ac.in