Model monitoring is the process of tracking the performance of machine learning models in production. It enables AI teams to identify, manage, and/or eliminate potential issues such as poor-quality predictions and technical performance, low latency, and inefficient use of resources. Model monitoring is important not only in achieving successful deployment. But also, in keeping the performance updated with accurate and relevant predictions.
