My Participation in ML challenge. 1st participation and it was very good learning!

Learnings:

1. Use of RFE for feature engineering.
2. Trying out different models simultaneously.
3. Finally using Bayesian Optimization.
4. Feature engineering is the crucial part because hyperparameter tuning can be taken care by Bayesian Optimization.
5. SMOTE and oversampling techniques seldom work for unbalanced datasets. Hit rate of <0.5%.