Consume ONNX models using Azure Machine Learning Service

It has been always difficult to consume TensorFlow or ONNX models without the help of tools like TensorFlow Serving or gRPC and all the fun that comes with protocol buffers. Hosting deep learning models to be consumed using REST was very hard although this is probably the most common approach application developers would start with. Microsoft has recently released Azure Machine Learning service which comes with heaps of features to facilitate development and deployment of machine learning models. One of those features is hosting ONNX models in docker containers to be consumed using REST. In this post, we go through an end to end workflow of hosting a sample ONNX model and consuming it from a .NET application.