ml-model-deployment

A collection of machine learning projects covering predictive modeling, classification, clustering, and NLP. Each project includes detailed analysis, feature engineering, and model evaluation. Some projects also have interactive Streamlit apps for real-time insights! 🚀

End-to-end MLOps pipeline for hotel booking demand forecasting. Includes modular components for data ingestion, model training, evaluation, versioning, and deployment. Features configuration-based execution, CI/CD with GitHub Actions, and automated logging and testing.

Unsupervised ML | Data cleaning → Imputation → Log transform → K-Means clustering → Streamlit dashboard. Deployed on Streamlit Cloud.