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General

0.3

  • Standalone example on microcontroller. XOR?

0.4

  • Setup documentation build (Sphinx?)
  • Consolidate error handling. Use EmlError, EML_PRE/POSTCONDITION, EML_CHECK_ERROR everywhere

Later

  • Implement some iterators like EML_APPLY(vector, 0, vector->length, func) and EML_MAP_INTO(in, out, 0, out->length, func);

audio

0.3

  • Add tests for melspectrogram
  • Unhardcode FFT length
  • Add some pipeline/processor. Short audio buffers in, feature extraction, normalization, classifier, predictions out.

0.4

  • Add an example. Wakeword detection? Keyword classification?
  • Implement low-level features. RMS, zero-crossings, spectral centroid, spectral flatness

nets

  • Add support for CNNs. 1D+2D convolutions, pooling (Keras).
  • Add support for RNNs. SimpleRNN, LSTM, GRU
  • Support quantized models (8 bits)
  • Supports strides and dilation in convolution layers

trees

0.3

  • Use floats by default

Probably

  • Support sklearn GradientBoostingClassifier
  • Support regression trees
  • Support weighted voting
  • Implement Isolation Forests (requires path/depths)

Maybe

  • Support XGBoost learning of trees
  • Support LightGBM learning of trees
  • Support CatBoost learning of trees
  • Support/Implement a Very Fast Decision Tree (VFDT) learning algorithm
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