TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments.
Core advantages (features)
TensorFlow Serving makes it easy to deploy new algorithms and experiments, while keeping the same server architecture and APIs. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data.
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