Data Mining and Machine Learning @ CSE, DIU

Fundamentals

• Lecture 2 - Basic
• Lecture 3 - Probability and Statistics of ML
• Lecture 4 - SMOTE, Random Undersampling and Oversampling
• Lecture 5 - Data Labelling
• Lecture 6 - Feature Selection (Ridge and LASSO)

Regression

• Lecture 7 - Linear Regression
• Lecture 8 - Polynomial Regression, Performance Metrics (MSE, RMSE, R2)

Classification

• Lecture 9 - Classification Algorithm (Logistic Regression, KNN)
• Lecture 10 - Decision Tree
• Lecture 11 - SVM
• Lecture 12 - Performance measures using confusion metrics

Clustering

• Lecture 13 - K-means Clustering
• Lecture 14 - Hierarchical Clustering
• Lecture 15 - DBSCAN
• Lecture 16 - Performance Metrics for Clustering