Machine Learning Operations (MLOps) is a methodology that unifies Machine Learning (ML) model solution development (the ML element) with ML solution operations (the Ops element). ModelOps, is a subset of MLOps that specifically focuses on the deployment, monitoring, and management of machine learning models in production environments. While MLOps is known to help data science processes with automation, ModelOps aims to bridge the gap between the development and operational phases of a model's lifecycle, enabling seamless integration of models into business processes and applications.
The ClearScape Analytics ModelOps product manages the operationalization of advanced analytics in Teradata Vantage.
The ClearScape Analytics ModelOps product also provides an easy-to-use web-based user interface (UI), a command line interface (CLI) and Python or R Software Development Kit (SDK) to handle advanced analytical model deployment and operationalization in Vantage using Analytics 1-2-3 process.