Projects

Machine Learning Engineering

A production-oriented Machine Learning experimentation platform that automates preprocessing, model comparison, hyperparameter optimization, explainability, experiment tracking, and deployment.

Unsupervised Learning • K-Means

An unsupervised Machine Learning application that groups customers into meaningful business segments using clustering techniques.

Regression • XGBoost

An end-to-end Machine Learning regression application for predicting residential property prices using feature engineering, model optimization, explainability, and interactive deployment.

Classification • Random Forest

A Machine Learning classification application that predicts whether a telecom customer is likely to leave the company based on historical customer behaviour.