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Training with Core ML 3

This is the sample code for my blog post series On-device training with Core ML.

Included are:

  • Dataset: a small dataset of 30 training images and 15 test images

  • iOS App: the source code of the demo app described in the blog post

  • Models: the empty and pre-trained models used by the app

    • TuriOriginal.mlmodel: the SqueezeNet classifier trained by Turi Create
    • HandsTuri.mlmodel: the TuriOriginal model but made updatable
    • HandsEmpty.mlmodel: like HandsTuri but with a classifier layer that has random weights
    • HandskNN.mlmodel: like TuriOriginal but with an untrained k-Nearest Neighbors classifier
  • Scripts:

    • make_nn.py: converts TuriOriginal.mlmodel to HandsTuri and HandsEmpty.mlmodel
    • make_knn.py: creates the k-Nearest Neighbor model, HandskNN.mlmodel
    • TuriCreate.ipynb: the notebook used to train TuriOriginal.mlmodel

Credits:

The source code is copyright 2019 M.I. Hollemans and licensed under the terms of the MIT license.

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Source code for my blog post series "On-device training with Core ML"

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