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XGBoost pipeline predicting >$50K income from the Adult Income dataset. Dual MLflow-tracked experiment tracks (1,500 feature combinations each) optimize F2-Score (recall-focused) and F1-Score (balanced) in parallel. F2: 0.94 recall / 0.48 precision. F1: 0.73 recall / 0.67 precision. Both reach ~0.91 AUC-ROC with minimal overfitting.
Updated
Sep 29, 2026
Jupyter Notebook
End-to-end oil supply chain daily demand prediction using Databricks, PySpark, Feature Store, MLflow, and Random Forest.
Updated
Oct 1, 2026
Python
Big Data and MLOps Final Project: Predicting arrest outcomes from Chicago crime data using Spark & MLOps
Updated
Mar 6, 2026
Jupyter Notebook
| Databricks MLOps Pipeline for dev and prod training and deploy |
Updated
Sep 15, 2026
Python
Playground repository for trying and testing various MLOps concepts with MLFlow
Updated
Aug 30, 2026
Python
My experiments with Databricks
Updated
Jan 24, 2026
Jupyter Notebook
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