TensorFlow Serving is a powerful system specifically built to serve machine learning models in production environments. Its flexibility and high-performance capabilities make deploying new algorithms and experiments a seamless process, all while maintaining a consistent server architecture and APIs. While it seamlessly integrates with TensorFlow models, it also offers easy extensions to serve other types of models and data, providing a versatile solution for deploying and managing machine learning models at scale in real-world scenarios.
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