Predicting the number of calories burned based on individual biometric and activity features using advanced ensemble machine learning techniques.
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Updated
Jun 4, 2025 - Jupyter Notebook
Predicting the number of calories burned based on individual biometric and activity features using advanced ensemble machine learning techniques.
Predicting product demand using Lasso, Ridge, and Stacking Regression for supply chain optimization.
A full-stack machine learning architecture for food delivery ETA prediction, leveraging a DVC-driven pipeline, automated CI/CD workflows, cloud artifact management, and LGBM-based stacked regression ensemble for high-fidelity time estimations.
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