VTU Online Courses

Introduction to Machine Learning - 12 weeks

@VTU COE

3.5

(11) 1942 Students

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What you will learn

Software

With the increased availability of data from varied sources there has been increasing attention paid to the various data driven disciplines such as analytics and machine learning. In this course we intend to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective. We will cover the different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms.

A brief introduction to machine learning

Preview 15:27

Supervised Learning

Preview 24:35

Unsupervised Learning

Preview 08:51

Reinforcement Learning

Preview 08:45

Probability Basics - 1

Preview 23:01

Probability Basics - 2

Statistical Decision Theory - Regression

Preview 41:04

Statistical Decision Theory - Classification

Multivariate Regression

Principal Components Regression

Preview 14:27

Partial Least Squares

Preview 14:34

Linear Classification

Preview 24:10

Logistic Regression

Preview 38:16

Linear Discriminant Analysis 1

Preview 16:21

Linear Discriminant Analysis 2

Preview 20:58

Linear Discriminant Analysis 3

SVM - Interpretation & Analysis

Preview 19:26

SVMs for Linearly Non Separable Data

Preview 30:55

SVM Kernels

Preview 17:49

SVM - Hinge Loss Formulation

Initialization, Training & Validation

Preview 31:13

Maximum Likelihood Estimate

Preview 14:27

Priors & MAP Estimate

Preview 13:07

Bayesian Parameter Estimation

Stopping Criteria & Pruning

Preview 23:36

Loss Functions for Classification

Preview 17:37

Categorical Attributes

Preview 13:45

Multiway Splits

Preview 16:27

Missing Values, Imputation & Surrogate Splits

Preview 21:31

Instability, Smoothness & Repeated Subtrees

Preview 13:07

Tutorial

Preview 20:01

Evaluation Measures I

Preview 17:46

Bootstrapping & Cross Validation

Preview 17:17

2 Class Evaluation Measures

Preview 20:54

The ROC Curve

Preview 26:02

Minimum Description Length & Exploratory Analysis

Preview 11:18

Introduction to Hypothesis Testing

Preview 19:51

Basic Concepts

Preview 27:33

Sampling Distributions & the Z Test

Preview 28:54

Student\'s t-test

Preview 16:37

The Two Sample & Paired Sample t-tests

Preview 16:51

Confidence Intervals

Preview 14:02

Bagging, Committee Machines & Stacking

Undirected Graphical Models - Introduction

Preview 37:54

Undirected Graphical Models - Potential Functions

Partitional Clustering

Preview 51:22

Hierarchical Clustering

Density Based Clustering

Preview 17:50

Gaussian Mixture Models

Preview 44:06

Expectation Maximization

Preview 32:24

Expectation Maximization Continued

Frequent Itemset Mining

Preview 27:21

The Apriori Property

Preview 41:26

Introduction to Reinforcement Learning

Preview 27:40

RL Framework and TD Learning

Preview 39:06

Solution Methods & Applications

Preview 12:56

Multi-class Classification

Preview 16:17

Punith Kumar H S

when the assignment and quiz will give sir

8 months ago

Punith Kumar H S

sir please send the assignment

7 months ago

Punith Kumar H S

sir please send the assignment

7 months ago

Punith Kumar H S

sir please send the assignment

7 months ago

SIDDESH DM

Sir how to download the certificate

7 months ago

Punith Kumar H S

guys you get any assignment and quiz

7 months ago

Punith Kumar H S

guys you get any assignment and quiz

7 months ago

Ansar Hansi

Send the assignment sir

7 months ago

Akshatha JS

Have any one registered for this exam in vtu portal by paying exam fee 1000

6 months ago