Lecture Notes || SNS Courseware

Subject Details

Dept : ECE

Sem : 5

Regul : 2019

Faculty : Dr.M.Sudha

phone : 8903444955

E-mail : sudha.m.ece@snsce.ac.in

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Lecture Notes

UNIT 1:

Testing Machine Learning Algorithms.

Weight Space-The Curse of Dimensionality

Machine Learning Process-Terminology

Types of Machine Learning

Goals and applications of machine learning

Definition of learning systems-

UNIT 2:

Regression: Linear Regression â€“Parametric Models

Multivariate Regression.

Classification: Bayesian Decision Theory

parametric and non-parametric methods

Logistic Regression- K-Nearest Neighbor classifier

Decision Tree based methods for classification and Regression

UNIT 3:

Hierarchical Clustering

Principal Component Analysis

EM algorithm,

K-means clustering

Introduction-Clustering

UNIT 4:

The Brain and The Neuron

Neural Networks

Perceptron-Training the perceptron

Perceptron Learning Algorithm

Multilayer Perceptron- Back Propagation

Dimensionality Reduction.

The Brain and The Neuron

UNIT 5:

Convolutional Networks

Recurrent Neural Networks

Bidirectional RNNs

Deep Recurrent Networks

Recursive Neural Networks

Applications â€“ Speech Recognition

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