Which additional readiness check should you recommend to the team?

You recently joined a machine learning team that will soon release a new project. As a lead on the project, you are asked to determine the production readiness of the ML components. The team has already tested features and data, model development, and infrastructure.

Which additional readiness check should you recommend to the team?
A . Ensure that training is reproducible
B . Ensure that all hyperparameters are tuned
C . Ensure that model performance is monitored
D . Ensure that feature expectations are captured in the schema

Answer: C

Explanation:

This is an important step in ensuring that the model has been developed and trained properly before it is put into production.

Model performance monitoring is also a crucial step to ensure that the model is working as expected after it is released, and to identify areas where further refinement may be necessary.

This would help to ensure that the model is performing well in production, and would also help to identify any issues that may arise over time.

Additionally, this would allow the team to better understand what changes need to be made in order to help the model perform optimally in production.