Course Summary and Next Steps

You should now have a better understanding of how to do the following:

• Validate input data and engineered data.
• Debug a ML model to make the model work.
• Optimize a working ML model.
• Discuss testing guidelines for ML models and pipelines.
• Monitor model metrics during development, launch, and production.

What’s Next

• View an end-to-end TFX example.
• Read papers by Googlers on productionizing ML:
  • Managing your Pipeline and preventing technical debt
  • The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction