An example machine learning workflow for signal modulation classification, built using RIA Hub Workflows
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RIA Hub Technical Demo

This repository demonstrates a full ML pipeline via Gitea Actions:

  • Recordings
    A collection of raw .npy radio recordings stored via Git LFS.

  • Workflows
    A CI pipeline that automatically:

    1. Builds a labeled dataset from raw recordings
    2. Trains a model on that dataset
    3. Optimizes the model and packages an inference application
  • Scripts

    • scripts/build_dataset.sh
      Reads through recordings/, applies preprocessing, and outputs training .npz or .csv files into data/.
    • scripts/train_model.sh
      Consumes data/, trains a PyTorch model, and writes checkpoints to checkpoints/.
    • scripts/build_app.sh
      Takes the best checkpoint and builds a small inference CLI or server in dist/.