Which service encompasses both model training and deployment in machine learning?

The correct choice is that Machine Learning Operations (MLOps) is the service that encompasses both model training and deployment in machine learning. MLOps is a set of practices that aims to streamline and automate the machine learning lifecycle, which includes the development, deployment, and operationalization of machine learning models. It provides a framework for collaboration between data scientists and operations teams, ensuring that models can be efficiently trained and then successfully deployed into production environments. MLOps addresses the challenges of maintaining model performance over time and managing the complexities associated with scaling machine learning solutions.

This choice stands out because it directly relates to the integration of machine learning models into operational workflows, facilitating continuous integration and delivery (CI/CD) specifically for AI and machine learning initiatives. In contrast, the other options focus on aspects that are either not comprehensive to the machine learning lifecycle or do not directly address both training and deployment. For instance, low code development refers to development platforms that allow users to create applications with minimal coding but does not specifically cover the machine learning model lifecycle. Machine learning support typically refers to assistance with existing models rather than the processes of training and deploying them. Linear modeling techniques are statistical methods used for predictive analysis and do not encompass the broader scope of model training and deployment as