Automating ML Workflows: Webhooks in Databricks with MLflow
<h1>A Use Case:</h1>
<p>Machine Learning (ML) is a dynamic field where models are continuously improved and updated. Consider an ML engineer at a tech company that deploys models for image recognition. Every time the engineer updates or improves a model, they must ensure it meets the required accuracy and performance metrics before it’s deployed into production.</p>
<p>Manually testing these models every time they’re updated can be tedious and error-prone. Moreover, waiting for scheduled tests may delay the deployment of an improved model, which could mean missing out on enhanced performance or user experience.</p>
<p><a href="https://awadrahman.medium.com/automating-ml-workflows-webhooks-in-databricks-with-mlflow-e0f9df849221"><strong>Click Here</strong></a></p>