ChessMania
End-to-end Chess MLOps pipeline — from PGN ingestion to Transformer-powered next-move prediction.
ChessMania is an end-to-end MLOps project that demonstrates every stage of the machine learning lifecycle using chess game data. It starts with a tabular ML baseline (XGBoost) and scales into Transformer-based sequence modelling.
Architecture
| Component | Implementation |
|---|---|
| Storage | MinIO (PGN / JSON / Parquet) |
| Orchestration | Apache Airflow (PGN parsing → Feature & Sequence extraction) |
| Data Validation | Great Expectations |
| ML Framework | XGBoost → GPT-style Transformer with LoRA/QLoRA |
| Experiment Tracking | MLflow (Accuracy, F1, AUC, Perplexity, MFU) |
| Serving | FastAPI + Uvicorn (Next-move prediction, Win probability) |
| Monitoring | Evidently AI (Feature drift + Structural/Move-sequence drift) |
Links: GitHub · Chess-DataOps · Chess-ontology