Modules / Lectures
Module NameDownload
Week_01_Assignment_01Week_01_Assignment_01
Week_02_Assignment_02Week_02_Assignment_02
Week_03_Assignment_03Week_03_Assignment_03
Week_04_Assignment_04Week_04_Assignment_04
Week_05_Assignment_05Week_05_Assignment_05
Week_06_Assignment_06Week_06_Assignment_06
Week_07_Assignment_07Week_07_Assignment_07
Week_08_Assignment_08Week_08_Assignment_08
Week_09_Assignment_09Week_09_Assignment_09
Week_10_Assignment_10Week_10_Assignment_10
Week_11_Assignment_11Week_11_Assignment_11
Week_12_Assignment_12Week_12_Assignment_12
Module NameDownloadDescriptionDownload Size
IntroductionSelf EvaluationPlease see the questions attached with the last module.25 kb
Hidden Markov ModelSelf EvaluationThis is a questionnaire covering all the modules and could be attempted after reading the full course.80 kb


Sl.No Chapter Name MP4 Download
1IntroductionDownload
2Feature Extraction - IDownload
3Feature Extraction - IIDownload
4Feature Extraction - IIIDownload
5Bayes Decision TheoryDownload
6Bayes Decision Theory (Contd.)Download
7Normal Density and Discriminant FunctionDownload
8Normal Density and Discriminant Function (Contd.)Download
9Bayes Decision Theory - Binary FeaturesDownload
10Maximum Likelihood EstimationDownload
11Probability Density EstimationDownload
12Probability Density Estimation (Contd.)Download
13Probability Density Estimation (Contd. )Download
14Probability Density Estimation ( Contd.)Download
15Probability Density Estimation ( Contd. )Download
16Dimensionality ProblemDownload
17Multiple Discriminant AnalysisDownload
18Multiple Discriminant Analysis (Tutorial)Download
19Multiple Discriminant Analysis (Tutorial )Download
20Perceptron CriterionDownload
21Perceptron Criterion (Contd.)Download
22MSE CriterionDownload
23Linear Discriminator (Tutorial)Download
24Neural Networks for Pattern RecognitionDownload
25Neural Networks for Pattern Recognition (Contd.)Download
26Neural Networks for Pattern Recognition (Contd. )Download
27RBF Neural NetworkDownload
28RBF Neural Network (Contd.)Download
29Support Vector MachineDownload
30Hyperbox ClassifierDownload
31Hyperbox Classifier (Contd.)Download
32Fuzzy Min Max Neural Network for Pattern RecognitionDownload
33Reflex Fuzzy Min Max Neural NetworkDownload
34Unsupervised Learning - ClusteringDownload
35Clustering (Contd.)Download
36Clustering using minimal spanning treeDownload
37Temporal Pattern recognitionDownload
38Hidden Markov ModelDownload
39Hidden Markov Model (Contd.)Download
40Hidden Markov Model (Contd. )Download

Sl.No Chapter Name English
1IntroductionDownload
Verified
2Feature Extraction - IDownload
Verified
3Feature Extraction - IIDownload
Verified
4Feature Extraction - IIIDownload
Verified
5Bayes Decision TheoryDownload
Verified
6Bayes Decision Theory (Contd.)Download
Verified
7Normal Density and Discriminant FunctionDownload
Verified
8Normal Density and Discriminant Function (Contd.)Download
Verified
9Bayes Decision Theory - Binary FeaturesDownload
Verified
10Maximum Likelihood EstimationDownload
Verified
11Probability Density EstimationDownload
Verified
12Probability Density Estimation (Contd.)Download
Verified
13Probability Density Estimation (Contd. )Download
Verified
14Probability Density Estimation ( Contd.)Download
Verified
15Probability Density Estimation ( Contd. )Download
Verified
16Dimensionality ProblemDownload
Verified
17Multiple Discriminant AnalysisDownload
Verified
18Multiple Discriminant Analysis (Tutorial)Download
Verified
19Multiple Discriminant Analysis (Tutorial )Download
Verified
20Perceptron CriterionDownload
Verified
21Perceptron Criterion (Contd.)Download
Verified
22MSE CriterionDownload
Verified
23Linear Discriminator (Tutorial)Download
Verified
24Neural Networks for Pattern RecognitionDownload
Verified
25Neural Networks for Pattern Recognition (Contd.)Download
Verified
26Neural Networks for Pattern Recognition (Contd. )Download
Verified
27RBF Neural NetworkDownload
Verified
28RBF Neural Network (Contd.)Download
Verified
29Support Vector MachineDownload
Verified
30Hyperbox ClassifierDownload
Verified
31Hyperbox Classifier (Contd.)Download
Verified
32Fuzzy Min Max Neural Network for Pattern RecognitionDownload
Verified
33Reflex Fuzzy Min Max Neural NetworkDownload
Verified
34Unsupervised Learning - ClusteringDownload
Verified
35Clustering (Contd.)Download
Verified
36Clustering using minimal spanning treeDownload
Verified
37Temporal Pattern recognitionDownload
Verified
38Hidden Markov ModelDownload
Verified
39Hidden Markov Model (Contd.)Download
Verified
40Hidden Markov Model (Contd. )Download
Verified


Sl.No Language Book link
1EnglishDownload
2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
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