AI Agent Skills

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

List of tools & datasets for anomaly detection on time-series data.

Scan all connected marketing platforms for statistically significant deviations from stored baselines — traffic drops, CPA spikes, deliverability collapse, budget overru…

Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, limits & quotas, configuration, and deployment. Use when tuning Doc…

Elastic ML anomaly detection — investigation/RCA, score explanation, job lifecycle troubleshooting, and job operations. Use when answering "what broke?"/"which entity?"/…

Use when the user has a known, already-observed anomaly in their data — a metric spike or drop, an outlier, an unexpected number — and wants its root cause diagnosed, no…

运用数据分析技术识别异常交易和潜在舞弊，涵盖本福特定律、趋势分析、重复检测和关联方筛查

A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic w…

A python library for user-friendly forecasting and anomaly detection on time series.

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific an…

A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anoma…

Find big moving stocks before they move using machine learning and anomaly detection

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana

Security log parsing, anomaly detection, SIEM query building, Sigma rule creation, and correlation rule development across Splunk, Elastic, QRadar, and Microsoft Sentinel