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This project forked from ksalama/gcp-ml-serving
Examples of how to serve ML models on GCP
Jupyter Notebook 33.95%
Shell 26.98%
Python 39.07%
gcp-ml-serving's Introduction
Examples included in this repository
- Serve Scikit-learn model as an API using Cloud ML Engine
- Serve TensorFlow model as an API using AppEngine + Endpoint
- Serve TensorFlow model as an API using TF Serving Container + Kubernetes Engine
- Serve TensorFlow SavedModel in Dataflow job, localy rather than calling an API
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