Industry specific framework of Feature Engineering in Machine Learning

ML-Project is an end-to-end machine learning project for regression tasks. It includes modules for data ingestion, preprocessing, exploratory data analysis (EDA), feature transformation, model training, and prediction pipelines. This project is structured to be modular, maintainable, and scalable for real-world ML applications.

Modular ML pipeline for student performance prediction — powered by FastAPI, Optuna, MLflow, PostgreSQL, and S3. Production-ready with YAML configs, Celery, DVC, and Docker support.