Anomaly Detection


Anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data.

Overview

Anomaly Detection for Dummies
Unsupervised anomaly detection for univariate & multivariate data.
anomaly-detection outlier-detection unsupervised-learning univariate
Deep Learning for Anomaly Detection: A Survey
We present a structured and comprehensive review of research methods in deep anomaly detection (DAD).
anomaly-detection survey research tutorial

Tutorials

Introduction to Anomaly Detection in Python
Learn how anomalies are created/generated, why they are important to consider while developing machine learning models, how they can be detected.
machine-learning scikit-learn tutorial article

Libraries

General
STUMPY: A Powerful and Scalable Python Library for Time Series
STUMPY is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks.
time-series anomaly-detection pattern-matching matrix-profile
Anomaly Detection Toolkit (ADTK)
A Python toolkit for rule-based/unsupervised anomaly detection in time series
anomaly-detection time-series unsupervised-learning library
Table of Contents
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