Train Machine learning model once and deploy it anywhere with ONNX optimization

Optimizing machine learning models for inference (or model scoring) is difficult if you want to get optimal performance on different kinds of platforms (cloud/edge, CPU/GPU, etc.), since each one has different capabilities and characteristics. A solution to train once in your preferred framework and run anywhere on the cloud or edge is needed. This is where ONNX comes in and this video will show you a hands-on example in azure machine learning using PyTorch and ONNX.

The notebook example utilized in the video:

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