production-mlops

QuantumFlow predicts cryptocurrency price movements before they happen by analyzing order book microstructure in real-time. From data ingestion to live trading signals, every component is production-hardened for hedge funds, algorithmic traders, and fintech platforms seeking systematic alpha generation through ML and quantitative rigor.

Governed scaffold for production classical ML on Kubernetes — scikit-learn, XGBoost, LightGBM, single team, 1-5 models. 38 encoded anti-patterns, multi-cloud (GKE/EKS), agent rules (AUTO/CONSULT/STOP), supply-chain security. LLM/GenAI and feature stores deferred by decision, each with a revisit trigger.

Automated end-to-end MLOps pipeline for predicting customer purchase likelihood of a wellness tourism package, enabling data-driven marketing through CI/CD-enabled model training and deployment.

End-to-end MLOps lifecycle implementation covering data ingestion, model training, experiment tracking, deployment, and monitoring using production best practices.