Day1
- Basic concepts of ML & ML process
- Linear Regression, KNN 

Day2
- Logistic Regression
- Decision Tree
- K-Fold Cross Validation
- Overfitting & Underfitting

Day3 
- Ensemble
- Random Forest & Bagging
- Adaboost & Boosting
- Stacking
