Data Scientist | ML Engineer | AI Specialist | Power BI Developper
🚀 Building robust ML pipelines from experimentation to production
MLOps Implementation: Dockerized microservices | CI/CD Pipelines | Model versioning with MLflow
Tech: Python, Flask, Heroku, Scikit-learn
📌 Live Demo
MLOps Features: Model monitoring | Data versioning (DVC) | Automated testing
Tech: R, Python, Streamlit, Docker
📌 Web App
Real-time monitoring: Data drift detection | Azure deployment
Tech: Power BI, Random Forest, Evidently
📌 Dashboard
- 💼 LinkedIn: noe-carème-fouotsa
- ✉️ Email: noecaremee@gmail.com
- 🌍 Portfolio: Portfolio
"Transforming data chaos into production-grade ML solutions with rigorous MLOps practices."