Practices

Collect performance data

Ways of deploying your model

How often do you deploy a model?

Keep a versioned model repository

Measure and proactively evaluate quality of training data

Testing through the ML pipeline

Business impact is more than just accuracy - understand your baseline

Regularly monitor your model in production

Monitor data quality

Automate the model lifecycle

Create a walking skeleton/steel thread

Appropriately optimise models for inference