TorchSig Tutorials
Hands-on examples and notebooks to get started with TorchSig
Tutorials
Learn TorchSig end-to-end: build datasets, apply transforms, train models, and run detection and classification workflows. Follow the notebooks below or explore the full examples collection on GitHub.
Browse All ExamplesNAML 2026 Tutorial
A complete, runnable walkthrough of TorchSig for the Naval Applied Machine Intelligence Laboratory (NAML) 2026 tutorial. Run it directly in your browser with Google Colab — no local install required.
Open in ColabExample Notebooks
Jupyter notebooks covering dataset creation, custom data ingestion (NumPy and SigMF), model training for modulation recognition, energy detection with YOLO, and reproducible dataset generation.
View on GitHubDocumentation
Full API reference, installation guides, and additional tutorials for datasets, transforms, and pretrained models.
Read the DocsPretrained Models
Tutorials and examples for the companion torchsig-models repository: pretrained architectures, training scripts, and YOLO/Anomalib adapters for signal classification and detection.
View Examples