What is model drift and how does it impact AI systems?

What is model drift and how does it impact AI systems?

Model drift refers to the changes in the statistical properties of a model's input data over time, which can lead to decreased performance.

Can you give me examples of model drift in real-world applications?

Sure! For instance, in finance, a model predicting stock prices may become less accurate due to changing market conditions.

How can we detect model drift?

Model drift can be detected using techniques like monitoring model performance metrics, statistical tests, and visualizations of input data distributions.

What strategies can be used to mitigate model drift?

To mitigate model drift, you can retrain models regularly, use adaptive learning techniques, and implement continuous monitoring.