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Keeping Your Model In Production
So you have built and deployed your model into production – now what? Building a model and taking it from experimentation to production is hard — and keeping it there is even harder! How do you know your models are doing well? And how do you know when you need to retrain your model?
During this workshop, we’ll tackle these questions through the lens of a credit card churn model use case.
We’ll cover the following steps:
- Ingest data from storage into Arize
- Set up monitoring around drift, data quality and performance
- Troubleshoot performance degradation and model drift
- Implement fairness checks in production
By the end of this workshop, you’ll have the ability to know when your model is broken, how to quickly find the root cause, and when to retrain.
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