Show sidebar
Show 30 45 60 75

Lecture 40 : Regression IV, by Pabitra Mitra

,

Lecture 10 : Decision Tree III, by Pabitra Mitra

,

Lecture 34: Clustering III, by Pabitra Mitra

,

Lecture 22 : Support Vector Machine I, by Pabitra Mitra

,

Lecture 32: Clustering I, by Pabitra Mitra

,

Lecture 11 : Decision Tree IV, by Pabitra Mitra

,

Lecture 8 : Decision Tree-I, by Pabitra Mitra

,

Lecture 36: Clustering V, by Pabitra Mitra

,

Lecture 13 : Bayes Classifier II, by Pabitra Mitra

,

Lecture 28: Artificial Neural Networks I, by Pabitra Mitra

,

Lecture 43 : Tutorial, by Pabitra Mitra

,

Introduction to Statistical Pattern Recognition, by P.S. Sastry

,

AdaLinE and LMS Algorithm; General Nonliner least-Squares Regression, by P.S. Sastry

,

Overview of Statistical Learning Theory; Empirical Risk Minimization, by P.S. Sastry

,

Backpropagation Algorithm; Representational Abilities of Feedforward Networks, by P.S. Sastry

,

Feedforward Networks for Classification and Regression; Backpropagation in Practice, by P.S. Sastry

,

Kernel Functions for Nonlinear SVMs; Mercer and Positive Definite Kernels, by P.S. Sastry

,

Bootstrap, Bagging and Boosting; Classifier Ensembles; Adaboost, by P.S. Sastry

,

Learning Weights in RBF Networks; K-Means Clustering Algorithm, by P.S. Sastry

,

Learning and Generalization; PAC Learning Framework, by P.S. Sastry

,

Linear Discriminant Functions for Multi-Class Case; Multi-Class Logistic Regression, by P.S. Sastry

,

Support Vector Regression and ?-Insensitive Loss Function, Examples of SVM Learning, by P.S. Sastry

,

Bayesian Estimation of Parameters of Density Functions, MAP Estimates, by P.S. Sastry

,

The Bayes Classifier for Minimizing Risk, by P.S. Sastry

,

Implementing Bayes Classifier; Estimation of Class Conditional Densities, by P.S. Sastry

,

Overview of Artificial Neural Networks, by P.S. Sastry

,

Consistency of Empirical Risk Minimization, by P.S. Sastry

,

Linear Discriminant Functions; Perceptron–Learning Algorithm and Convergence Proof, by P.S. Sastry

,

Bayesian Estimation Examples; The Exponential Family of Densities and ML Estimates, by P.S. Sastry

,

No Free Lunch Theorem; Model Selection and Model Estimation; Bias-Variance Trade-Off, by P.S. Sastry

,