A managed, end-to-end environment that supports the development, training, deployment, and operationalization of machine learning models. It provides integrated tools, scalable compute resources, and automation capabilities for data preparation, model experimentation, training, hyperparameter tuning, and performance monitoring. Designed to streamline the entire machine learning lifecycle, such platforms enable collaboration across teams, ensure reproducibility, and support continuous integration and delivery of ML models into production environments.