anomaly-detection-resources

Why we included this project

Anomaly detection spans tabular, time-series, graph, and text data, and this index organizes the field into those strands so you can find the right starting point without hours of scattered searching. It collects books, tutorials, benchmark papers, online courses, datasets, and open-source toolkits, and the maintainer also wrote PyOD, so the picks come from someone who has actually built and shipped detection tooling. The late-2025 update added LLM and VLM work, which matters if you are weighing whether large language models belong in your fraud, intrusion, or defect-detection stack. Treat it as a map of the field rather than software to deploy; it points you to the benchmarks and libraries worth trying.