Week - 1 |
Introduction to Machine Learning |
Week - 2 |
Linear Regression Model |
Week - 3 |
Variable Selection and Regularization |
Week - 4 |
Cross-Validation and Model Evaluation |
Week - 5 |
Supervised Learning Methods |
Week - 6 |
Logistic and Ordered Regression Models |
Week - 7 |
k-nearest Neighbors Algorithm |
Week - 8 |
Decision Trees |
Week - 9 |
Ensemble Learning Methods |
Week - 10 |
Random Forests |
Week - 11 |
Unsupervised Learning Methods |
Week - 12 |
k-means Algorithm |
Week - 13 |
Principal Component Analysis |
Week - 14 |
Project Presentations |