Google has just moved to a production release of TensorFlow Serving, its open source library for serving machine-learned models in production environments. A beta version of the technology was released in February.Part of Google’s TensorFlow machine intelligence project, the TensorFlow Serving 1.0 library is intended to aid the deployment of algorithms and experiments while maintaining the same server architecture and APIs. TensoFlow Serving lets you push out multiple versions of models over time, as well as roll them back.[ Learn how to write apps that take full advantage of machine learning: Data in, intelligence out: Machine learning pipelines demystified • Google’s machine-learning cloud pipeline explained • R and Python drive SQL Server 2017 into machine learning. | Keep up with hot topics in programming with InfoWorld’s App Dev Report newsletter. ]
The library of course integrates with TensorFlow learning models, but it can also be extended to serve other model types.To read this article in full or to leave a comment, please click here

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