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Is ModelOps important to manage AI/ML models? – By Aditya Abeysinghe What is ModelOps? Machine learning (ML) is used in many platforms today. ML modelling algorithms and ML-based programming have made it easier over the last decade to find the best ML model for a given app by training data. Different stages are used in the deployment of a ML model or an Artificial Intelligence (AI) model.  Finding suitable datasets, preparing data chosen to train models, training models, testing models, deploying the model, and monitoring the deployed model are some common stages used. These stages of deploying and monitoring models is called Model Operationalization (ModelOps). Why ModelOps? As each phase of the deployment of models is monitored by ModelOps, issues in a phase can be identified earlier and mitigated before they are passed to other phases. This could reduce risks and costs associated with rectifying issues in later phases. Also, ...