To check out the project open .ipybn file.
Data Analysis and Machine Learning with Python
- EDA with ECDF and Correlation analysis.
- Preprocessing and Feature engineering.
- L1 (Lasso) Regression and Random Forest Regressor with scikit-learn backed up by cross-validation, grid search and plots of feature importance.
Libraries used: numpy, pandas, missingno, matplotlib + seaborn and sklearn.