Model Serving

Model serving refers to the deployment of machine learning models in a production environment, enabling them to make predictions on new data in real-time. This process involves exposing the model through an API or user interface, allowing applications to interact with it seamlessly. Key characteristics of model serving include scalability, reliability, and the ability to handle multiple requests concurrently. Common use cases include serving recommendation systems, fraud detection models, and image recognition services, facilitating immediate insights from data. Efficient model serving is crucial for integrating AI into business processes and enhancing user experiences.