In this set of notebook examples, we show examples for building and editing mlmodels via coremltools.
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Setting per channel scale image pre-processing
This notebook shows how an mlmodel can be edited after conversion, to add to it a per channel scale pre-processing layer. -
Power iteration algorithm using a neural network Core ML model
This notebook shows how to build an mlmodel from scratch using the neural networkbuilder
API in coremltools. In particular, this examples shows how a non-neural network algorithm involving control flow features can still be expressed as an mlmodel. The feature of usingflexible shaped
inputs is also touched upon at the end of the notebook.