Lecture Notes || SNS Courseware

Subject Details

Dept : CSE

Sem : 5

Regul : 2019

Faculty : Jacquelin Anushya

phone : NIL

E-mail : janushya.p.cse@snsct.org

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Lecture Notes

UNIT 1:

Machine Learning process- preliminaries, testing

turning data into Probabilities, and Statistics for Machine Learning

Probability theory -Bayesian Decision Theory.

UNIT 2:

Introduction - Linear Models for Regression – Linear Regression Models and Least Squares

Subset Selection – Shrinkage Methods

UNIT 3:

bayesian neural net

regularization

interpretation

fitting neural network

boosting

neural network representation

multilayer networks

UNIT 4:

Unsupervised Learning - Introduction

Association rules

Apriori Algorithm

K- means

Guassian Mixture

Self Organising Maps

Independent Component Analysis

UNIT 5:

Reinforcement Introduction

Model based Learning

Temporal Difference Learning

Generalization

Lecture Notes