Model serving is the process of deploying machine learning models so they can be accessed and used by applications or users for making predictions in real-time or batch modes. It plays a crucial role in taking trained models and making them available for inference, allowing businesses and developers to integrate machine learning into their systems effectively. Proper model serving ensures scalability, reliability, and efficiency in delivering predictions based on incoming data.
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