Lecture Notes || SNS Courseware

Subject Details

Dept : ECE

Sem : 5

Regul : 2019

Faculty : P.Ramya

phone : NIL

E-mail : ramya.ece.snsce@gmail.com

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Lecture Notes

UNIT 1:

Goals and applications of machine learning

Definition of learning systems

Types of Machine Learning

Machine Learning Process-Terminology-Weight Space

The Curse of Dimensionality

Testing Machine Learning Algorithms

UNIT 2:

Regression: Linear Regression –Parametric Models

Multivariate Regression

Classification: Bayesian Decision Theory-parametric and non-parametric methods

Multivariate Classification-Logistic Regression

K-Nearest Neighbor classifier

Decision Tree based methods for classification and Regression- Ensemble methods.

UNIT 3:

Introduction

Clustering-K-means clustering

EM algorithm

Hierarchical Clustering

Principal Component Analysis

Probabilistic PCA

Dimensionality Reduction

Lecture Notes