Model deployment. This step involves the execution of the model in a compute resource, in which the algorithm runs and is published to work with it on a trained and functional state.
Model deployment. The last step is to integrate the final model into the deployment environment. Scalability, costs, security, and integration capabilities are factors to be considered.
