Predict Drug Shortages with AI: Live API & ML System DemoPredict Drug Shortages with AI: Live API & ML System Demo
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Medicine Supply Chain Disruption Predictor
Built a production-ready ML system that predicts drug shortage risk using real FDA data. Collected and cleaned 1703 real drug shortage records, trained an XGBoost model, and deployed it as a live REST API — accessible to anyone worldwide.
The biggest challenge was identifying and removing 6 sources of data leakage that were causing fake 100% accuracy. After fixing this, the model delivers honest, generalisable predictions.
The entire system is containerised with Docker, automatically rebuilt and redeployed via a Jenkins CI/CD pipeline on every code push, and visualised through an interactive Power BI dashboard.
Result: A complete ML + DevOps project — from raw data to live deployed API — built independently in under 2 weeks.
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Anil's avatar
Really strong work here. Identifying and fixing data leakage that led to false 100% accuracy is not easy, and it shows deep ML understanding. The combination of XGBoost, Docker, Jenkins, and Power BI makes this a well-rounded, real-world solution.
Istiak Ahmed's avatar
great job👌
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