A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

A unified framework for machine learning with time series

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

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

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

Merlion: A Machine Learning Framework for Time Series Intelligence

STUMPY is a powerful and scalable Python library for modern time series analysis

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

A machine learning toolkit for log parsing [ICSE'19, DSN'16]

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

TODS: An Automated Time-series Outlier Detection System

A Python Library for Graph Outlier Detection (Anomaly Detection)

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

Unsupervised time series anomaly detection library

RNN based Time-series Anomaly detector model implemented in Pytorch.

Anomaly Detection and Correlation library

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

A Python toolkit for rule-based/unsupervised anomaly detection in time series