Taking a machine learning model to production from the proof of concept stage is a complex journey. Deploying the model is only the tip of the iceberg when it comes to operationalizing machine learning (ML) models. After the initial deployment, maintaining deployed models and continuously improving them requires specialized tools and systems. ML model monitoring …