Notebook Examples

These notebooks provide guided, runnable examples for the main eegclassify workflows. They are rendered in the documentation and also kept as source notebooks under the repository's notebooks/ directory.

Each training notebook starts with FAST_DEV_RUN=True. That setting keeps examples short enough for a first pass while preserving the same configuration cells used for longer runs.

Available Examples

• Data postprocessing: download, convert, summarize, and compare processed EEG arrays.
• TensorFlow reproduction: train and evaluate TensorFlow/Keras classifiers.
• PyTorch reproduction: train and evaluate PyTorch classifiers.
• JAX/Flax reproduction: train and evaluate JAX/Flax classifiers.

For scripted runs, use the commands in Reproduce Results.