End-to-End ML Pipeline Project with FastAPI and CI for Learning MLOps
Published:Dec 28, 2025 12:16
•1 min read
•r/learnmachinelearning
Analysis
This project is a great initiative for learning MLOps by building a production-style setup from scratch. The inclusion of a training pipeline with evaluation, a FastAPI inference service, Dockerization, CI pipeline, and Swagger UI demonstrates a comprehensive understanding of the MLOps workflow. The author's focus on real-world issues and documenting fixes is commendable. Seeking feedback on project structure, completeness for a real MLOps setup, and potential next steps for production is a valuable approach to continuous improvement. The project provides a practical learning experience for anyone looking to move beyond notebooks in machine learning deployment.
Key Takeaways
- •Practical MLOps learning through building a complete pipeline.
- •Focus on real-world deployment challenges and solutions.
- •Importance of CI/CD and testing in machine learning projects.
Reference
“I’ve been learning MLOps and wanted to move beyond notebooks, so I built a small production-style setup from scratch.”