model@run

The term "model@run" typically refers to executing or deploying a trained machine learning model in a practical setting. It involves applying the developed model to new data to generate predictions or insights, often during the actual operation of a system. Think of it as taking a trained recipe and using it to produce a dish in real-time. This process is essential for putting AI solutions into action, whether for recommending products, detecting fraud, or forecasting trends, ensuring that the trained model delivers useful results in real-world scenarios.