Your team is working on an NLP model and has just operationalized the first model. Your team makes updates to the model, overwrites the original model, and puts this new model into operation. However, one of the teams using the model has seen a decrease in performance and is asking to use the original model.
What critical error did your team make?
- They did not have data governance in place
- They did not practice model versioning and keep all versions of the model
- They did not have a model retraining pipeline that took into account models
- They did not practice model iteration and properly iterate on the model
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