This will appeal to any developer that wants to deploy machine learning models on macOS or iOS and get the most out of the hardware (Metal w/Core ML). > The do

This will appeal to any developer that wants to deploy machine learning models on macOS or iOS and get the most out of the hardware (Metal w/Core ML). > The docs [1] also seem to imply they're using transfer learning from more robust models for their image classifier I read that as a recommendation for the minimum number of training samples per label (e.g. 10 photos w/leopard tagged). Apple's Turi Create [1] also also been getting some love these last few months to add support for exporting to Core ML. [1] https://github.com/apple/turicreate https://github.com/apple/turicreate