NOC:Data Mining


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