Part two of my pandemic project for deploying Pytorch to iOS via Core ML, this tutorial consisting of a model with trainable spectrogram layers for analyzing live audio captured via microphones. The trickiest part is the Core ML conversion step, which is validated via unit tests as a starting point for more complex ML-enabled iOS apps.
Any feedback on improving the tutorial and the app would be appreciated!
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