A compilation of my machine learning notebook. Please read the notebook in https://nbviewer.org/ to get a better format and see the visualization.
- titanic-project: EDA, feature engineering (impute missing values, standardization, one-hot encoding, feature selection by Mutual Information using Pipeline and ColumnTransformer), model selection (Repeated KFolds CV), hyperparameter tuning (GridSearchCV), model evaluation (confusion matrix, precision, recall)