- Model Refreshes
Understand different methods to refresh machine learning models deployed as serverless functions, including redeployment, timeouts, new function versions, and triggers. Learn best practices to maintain model accuracy and handle updates smoothly in production environments.
We'll cover the following...
We'll cover the following...
Updating models
We’ve deployed sklearn and Keras models to production using Cloud Functions, but the current implementations of these functions use static model files that will not change over time. It’s usually necessary to make changes to models overtime to ensure that the accuracy of the models does not drift too ...