Unsupervised ML | Data cleaning → Imputation → Log transform → K-Means clustering → Streamlit dashboard. Deployed on Streamlit Cloud.
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Updated
Apr 8, 2026 - Jupyter Notebook
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ml-model-deployment
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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.
python machine-learning jupyter-notebook ci-cd forecasting data-pipeline model-evaluation data-ingestion hotel-booking project-structure mlops github-actions mlops-pipeline ml-model-deployment
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Updated
Apr 20, 2025 - Jupyter Notebook
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