Topic

No. of hours

Lecture

Tutorial/Practical

Introduction.

3

3

-

Supervised Learning.

3

3

-

Bayesian Decision Theory.

3

3

-

Parametric Methods.

3

3

-

Multivariate Methods.

3

3

-

Dimensionality Reduction.

3

3

-

Clustering.

3

3

-

 Nonparametric Methods.

3

3

-

Decision Trees.

3

3

-

Linear Discrimination.

3

3

-

Multilayer Perceptrons.

3

3

-

Local Models.

3

3

-

 Kernel Machines.

3

3

-

 Bayesian Estimation.

3

3

-