Machine Learning Engineer
Published:
Earned the Machine Learning Engineer certification from DataCamp.
Topics Covered
- Supervised Learning: scikit-learn and predictive modeling
- MLOps: Concepts, deployment, lifecycling, and monitoring in production
- MLflow: Tracking, projects, models, and model registry
- DevOps for ML: Shell scripting, Docker, CI/CD with GitHub Actions
- Data Pipelines: ETL/ELT in Python, data quality (Great Expectations), data versioning (DVC)
- Monitoring: Data and concept drift, model degradation detection