Bring CNTK model evaluation to this library about machinelearning HOT 5 CLOSED

re: @glebuk question on priority. I would prioritize Eval. There are lots of other resources compute and otherwise that we use for training. Eval is where we are trying to use this in applications. Being able to use the CNTK models without all this or this or this.

Plus those are adding about 1GB+ to our deployments. If that can be a smaller, managed code, eval only deployment that works with nothing more than nuget add - that would bring model eval ML as a first-class citizen to using it in our .Net app dev.

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Ryan, thanks for the suggestion! Integration of deep learning is in our roadmap longer term.
It would be interesting to see what scenarios you would be interested in.
Would it be useful if you could train CNTK models in ML.NET as well?
Are you using any hybrid models that combine CNTK with a general-purpose ML algorithms?

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I would love to have the evaluation in this as well. We work a lot with developers that know how to build regular software, but don't train models themselves.

One scenario I can think of is that you train a model and export it to ONNX and then load it in ML.NET so that you can make predictions using that model.

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+1 For training CNTK in ML.NET

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DRI RESPONSE: We implemented TensorFlow and Onnx transforms, which allow you to score models. You can always convert CNTK model to ONNX and use it.

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