Lecture Notes || SNS Courseware

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Subject Details

Dept : BIO

Sem : 5

Regul : R2019

Faculty : N.Jayashree

phone : NIL

E-mail : jayashree.n.ece@snsct.org

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Lecture Notes

UNIT 1:

Terminology-Weight Space

Learning Algorithms

Definition of learning systems Goals and applications of machine learning

Types of Machine Learning Machine Learning Process

Learning Algorithms

UNIT 2:

Parametric Models- Multivariate Regression

Classification: Bayesian Decision Theory parametric and non-parametric methods

K-Nearest Neighbor classifier

Decision Tree based methods for classification and Regression Ensemble methods

Regression: Linear Regression

UNIT 3:

Introduction

Principal Component Analysis

Clustering-K-means clustering

EM algorithm

Hierarchical Clustering

Probabilistic PCA

Introduction

UNIT 4:

The Brain and The Neuron

Back Propagation Dimensionality Reduction

Perceptron-Training the perceptron

Perceptron Learning Algorithm

Perceptron-Training the perceptron

Neural Networks

UNIT 5:

Convolutional Networks

Recurrent Neural Networks

Bidirectional RNNs

Applications Speech Recognition

Deep Recurrent Networks

Announcements

Sep

Write Applications of AIML in detail

Recent Files

Sep

Terminology-Weight Space

Sep

Learning Algorithms

Sep

Learning Algorithms

Sep

Definition of learning systems Goals and applications of machine learning

Sep

Types of Machine Learning Machine Learning Process

Sep

Learning Algorithms

Lecture Notes

Announcements

Recent Files

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