226 Open source projects that are alternatives of or similar to Awesome Aiops

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Anomaly detection related books, papers, videos, and toolboxes

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Resources for working with time series and sequence data

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A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Transfer learning for time series classification

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This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

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Merlion: A Machine Learning Framework for Time Series Intelligence

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List of awesome papers about time series, mainly including algorithms based on machine learning | 收录时间序列分析中各个研究领域的高水平文章，主要包含基于机器学习的算法

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

Anomaly detection

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Hastic data management server for analyzing patterns and anomalies from Grafana

Detect EEG artifacts, outliers, or anomalies using supervised machine learning.

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A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

AtsPy: Automated Time Series Models in Python (by @firmai)

Useful Toolbox for Anomaly Detection

Machine Learning Lectures at the European Space Agency (ESA) in 2018

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An Integrated Experimental Platform for time series data anomaly detection.

Contains the thorough experiments made for a FloydHub article on Anomaly Detection

Healthbot configuration examples. Scripts to manage Healthbot. Closed loop automation. Healthbot building blocks description and troubleshooting guide

Thio - a playground for real-time anomaly detection

A unified framework for machine learning with time series

SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats.

Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

This repository is the PyTorch implementation of GAN Ensemble for Anomaly Detection.

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

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iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

Faster and more precisely than Grad-CAM

使用极端值理论(Extreme Value Theory)实现阈值动态自动化设置

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

A python multi-variate time series prediction library working with sklearn

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).