Introduction to Machine Learning

Course Duration: 12 Weeks

@VTU COE

4.0
(8) 1710 Students

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.

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Probability Basics - 1
Preview 23:01
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Probability Basics - 2
Preview 28:51

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Linear Algebra - 1
Preview 21:39
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Linear Algebra - 2
Preview 20:16

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Statistical Decision Theory - Regression
Preview 41:04
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Statistical Decision Theory - Classification
Preview 19:20
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Bias-Variance
Preview 17:06

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Linear Regression
Preview 23:39
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Multivariate Regression
Preview 29:51

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Subset Selection 1
Preview 15:48
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Subset Selection 2
Preview 23:43
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Shrinkage Methods
Preview 14:52
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Principal Components Regression
Preview 14:27
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Partial Least Squares
Preview 14:34

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Linear Classification
Preview 24:10
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Logistic Regression
Preview 38:16
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Linear Discriminant Analysis 1
Preview 16:21
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Linear Discriminant Analysis 2
Preview 20:58
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Linear Discriminant Analysis 3
Preview 24:59
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Weka Tutorial
Preview 25:20

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Optimization
Preview 35:50

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Perceptron Learning
Preview 32:00
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SVM - Formulation
Preview 15:46
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SVM - Interpretation & Analysis
Preview 19:26
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SVMs for Linearly Non Separable Data
Preview 30:55
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SVM Kernels
Preview 17:49
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SVM - Hinge Loss Formulation
Preview 14:41

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Early Models
Preview 29:43
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Backpropogation I
Preview 25:13
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Backpropogation II
Preview 21:30
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Initialization, Training & Validation
Preview 31:13

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Maximum Likelihood Estimate
Preview 14:27
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Priors & MAP Estimate
Preview 13:07
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Bayesian Parameter Estimation
Preview 21:53

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Introduction
Preview 18:07
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Regression Trees
Preview 30:56
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Stopping Criteria & Pruning
Preview 23:36
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Loss Functions for Classification
Preview 17:37
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Categorical Attributes
Preview 13:45
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Multiway Splits
Preview 16:27
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Missing Values, Imputation & Surrogate Splits
Preview 21:31
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Instability, Smoothness & Repeated Subtrees
Preview 13:07
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Tutorial
Preview 20:01

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Evaluation Measures I
Preview 17:46
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Bootstrapping & Cross Validation
Preview 17:17
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2 Class Evaluation Measures
Preview 20:54
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The ROC Curve
Preview 26:02
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Minimum Description Length & Exploratory Analysis
Preview 11:18

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Introduction to Hypothesis Testing
Preview 19:51
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Basic Concepts
Preview 27:33
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Sampling Distributions & the Z Test
Preview 28:54
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Student\'s t-test
Preview 16:37
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The Two Sample & Paired Sample t-tests
Preview 16:51
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Confidence Intervals
Preview 14:02

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Bagging, Committee Machines & Stacking
Preview 31:13
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Boosting
Preview 35:51
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Gradient Boosting
Preview 40:23
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Random Forest
Preview 05:46

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Naive Bayes
Preview 29:03
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Bayesian Networks
Preview 40:00
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Undirected Graphical Models - Introduction
Preview 37:54
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Undirected Graphical Models - Potential Functions
Preview 27:38
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Hidden Markov Models
Preview 10:31
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Variable Elimination
Preview 32:32
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Belief Propagation
Preview 16:36

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Partitional Clustering
Preview 51:22
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Hierarchical Clustering
Preview 15:20
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Threshold Graphs
Preview 33:37
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The BIRCH Algorithm
Preview 21:10
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The CURE Algorithm
Preview 20:01
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Density Based Clustering
Preview 17:50

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Gaussian Mixture Models
Preview 44:06
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Expectation Maximization
Preview 32:24
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Expectation Maximization Continued
Preview 38:19

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Spectral Clustering
Preview 64:32

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Learning Theory
Preview 82:50

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Frequent Itemset Mining
Preview 27:21
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The Apriori Property
Preview 41:26

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Introduction to Reinforcement Learning
Preview 27:40
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RL Framework and TD Learning
Preview 39:06
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Solution Methods & Applications
Preview 12:56

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Multi-class Classification
Preview 16:17
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Punith Kumar H S

when the assignment and quiz will give sir

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Punith Kumar H S

sir please send the assignment

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Punith Kumar H S

sir please send the assignment

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Punith Kumar H S

sir please send the assignment

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SIDDESH DM

Sir how to download the certificate

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Punith Kumar H S

guys you get any assignment and quiz

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Punith Kumar H S

guys you get any assignment and quiz

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Ansar Hansi

Send the assignment sir

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Akshatha JS

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

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Tanya Agarwal

credit points for this course?

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Tanya Agarwal

credit points for this course?

2 weeks ago
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Tanya Agarwal

credit points for this course?

2 weeks ago
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Tanya Agarwal

credit points for this course?

2 weeks ago
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Tanya Agarwal

credit points for this course?

2 weeks ago
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Tanya Agarwal

credit points for this course?

2 weeks ago
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Tanya Agarwal

credit points for this course?

2 weeks ago
0
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Tanya Agarwal

credit points for this course?

2 weeks ago
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Tanya Agarwal

credit points for this course?

2 weeks ago
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Punith Kumar H S

3 credit points

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Punith Kumar H S

3 credit points

6 days ago

4.0

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Kavya S

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when assignment and quiz is going to be uploaded

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Tanya Agarwal

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credit points for this course?

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Ansar Hansi

3 weeks ago

when assignment and quiz is going to be uploaded

Meet Your Instructor
@VTU COE
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Instructor
0.0 Rating
40 Students
718 Courses
About Instructor

VTU is one of the largest Technological Universities in India with 24 years of Tradition of excellence in Engineering & Technical Education, Research and Innovations. It came into existence in the year 1998 to cater the needs of Indian industries for trained technical manpower with practical experience and sound theoretical knowledge.

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Free

  • Course Duration
    35 h 25 m 22 s
  • Course Level
    Intermediate
  • Student Enrolled
    1710
  • Language
    English
This Course Includes
  • 35 h 25 m 22 s Video Lectures
  • 1 Quizzes
  • 0 Assignments
  • 0 Downloadable Resources
  • Full Lifetime Access
  • Certificate of Completion