A complete end-to-end machine learning pipeline to predict employee salaries (USD) using job-related features. Includes automated EDA, robust preprocessing, ML model training with MLflow, drift detection with Evidently AI, and a Flask-based web app for both single and batch predictions.

Industrialisation du modèle de scoring crédit, intégrée dans le projet global de plateforme de scoring MLOps.

End-to-end demand forecasting and inventory optimization with Databricks - multi-modal ML (time series, images, tabular), LightGBM, MAPIE conformal prediction and MLOps for retail and fashion.

La plateforme de scoring automatisé avec MLOps vise à fournir un système intelligent, scalable et traçable pour : Évaluer le risque de crédit des prospects, Détecter anomalies et fraudes dans les transactions, Automatiser les rapports de conformité (KYC, AML).

End-to-end fraud detection system with MLflow, FastAPI, drift detection, and automated retraining

Scalable MLOps platform for real-time drift detection and monitoring across multiple ML models. Built with a microservices architecture using FastAPI, Qdrant (Vector DB), Evidently AI, and Prometheus/Grafana