Common Industry Use Cases

Use-case specific examples of how to leverage Arize to troubleshoot your ML models.

Learn how to set up proactive monitors for chargebacks (false negative rate) and false positive transactions for your credit card fraud model.

Troubleshoot bad data quality, drifting features, and low-performing cohorts of your ad click-through rate model.

Identify where your demand forecasting model is over/under predicting and for which items/locations your model might require retraining.

Improve your customer lifetime value model by identifying low-performing cohorts and drifting features.

Learn how to set up a collaborative filtering model, normally used in recommendation engines, in the Arize platform.

Learn how to troubleshoot a search ranking model using a rank-aware evaluation metric

Contact us at [email protected] to contribute an example to the list or request a tutorial!