NPTEL : NOC:Data Mining (Computer Science and Engineering)

Co-ordinators : Prof. Pabitra Mitra


Lecture 1 - Introduction, Knowledge Discovery Process

Lecture 2 - Data Preprocessing - I

Lecture 3 - Data Preprocessing - II

Lecture 4 - Association Rules

Lecture 5 - Apriori algorithm

Lecture 6 - Rule generation

Lecture 7 - Classification

Lecture 8 - Decision Tree - I

Lecture 9 - Decision Tree - II

Lecture 10 - Decision Tree - III

Lecture 11 - Decision Tree - IV

Lecture 12 - Bayes Classifier - I

Lecture 13 - Bayes Classifier - II

Lecture 14 - Bayes Classifier - III

Lecture 15 - Bayes Classifier - IV

Lecture 16 - Bayes Classifier - V

Lecture 17 - K Nearest Neighbor - I

Lecture 18 - K Nearest Neighbor - II

Lecture 19

Lecture 20

Lecture 21

Lecture 22 - Support Vector Machine - I

Lecture 23 - Support Vector Machine - II

Lecture 24 - Support Vector Machine - III

Lecture 25 - Support Vector Machine - IV

Lecture 26 - Support Vector Machine - V

Lecture 27 - Kernel Machines

Lecture 28 - Artificial Neural Networks - I

Lecture 29 - Artificial Neural Networks - II

Lecture 30 - Artificial Neural Networks - III

Lecture 31 - Artificial Neural Networks - IV

Lecture 32 - Clustering - I

Lecture 33 - Clustering - II

Lecture 34 - Clustering - III

Lecture 35 - Clustering - IV

Lecture 36 - Clustering - V

Lecture 37 - Regression - I

Lecture 38 - Regression - II

Lecture 39 - Regression - III

Lecture 40 - Regression - IV

Lecture 41 - Dimensionality Reduction - I

Lecture 42 - Dimensionality Reduction - II

Lecture 43 - Tutorial

Lecture 44 - Live Session