This repository contains simple usage examples for basic machine learning libraries. These notebooks are tested in Colab.

XGB_classification_titanic.ipynb

• A supervised ML classification example using XGBoost (GPU), sklearn (pipeline & auto hyperparameter tuning) & SMOTE on the titanic dataset. (Custom feature extraction/engineering & SMOTE excluded from pipeline.)

imblearn_XGB_titanic.ipynb

• A supervised ML classification example using XGBoost (GPU) & sklearn (auto-hyperparameter tuning & custom transformer) with imblearn pipeline & SMOTE on the titanic dataset. (Full pipeline)

XGB_regression_kc_house.ipynb

• A supervised ML regression example using XGBoost (GPU) & sklearn (pipeline & auto hyperparameter tuning) on the King county house sales dataset.

cust_trans_XGB_kc_house.ipynb

• A supervised ML regression example using XGBoost (GPU) & sklearn (pipeline, custom transform & auto hyperparameter tuning) on the King county house sales dataset. (Full pipeline)

clustering_iris.ipynb

• An unsupervised ML clustering example using sklearn on the iris dataset.

CNN_classification_MNIST.ipynb

• A supervised ML classification example using CNN from Keras & Kerastuner (auto hyperparameter tuning) on the MNIST dataset.