228 Open source projects that are alternatives of or similar to Machine Failure Detection

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

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

Hastic data management server for analyzing patterns and anomalies from Grafana

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

A PyTorch implementation of the Deep SVDD anomaly detection method

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

A Deep Graph-based Toolbox for Fraud Detection

A log analysis toolkit for automated anomaly detection [ISSRE'16]

Anomaly detection related books, papers, videos, and toolboxes

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.

Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

Anomaly detection implemented in Keras

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Anomaly detection

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

Python module for hyperspectral image processing

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)

Tidy anomaly detection

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

Thio - a playground for real-time anomaly detection

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

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

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

An Integrated Experimental Platform for time series data anomaly detection.

High-performance time series algorithms for Ruby

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

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

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

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

Anomaly Detection and Correlation library

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

👑 Python factor analysis library (PCA, CA, MCA, MFA, FAMD)

An open-source, low-code machine learning library in Python

Source code for the 2019 IEEE TIFS paper "PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition"

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

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.

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).

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

Python code for common Machine Learning Algorithms

A lean C++ library for working with point cloud data

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

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

Merlion: A Machine Learning Framework for Time Series Intelligence

A large collection of system log datasets for AI-powered log analytics

Fusion ICA Toolbox (MATLAB)

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

A thesis submitted for the degree of Master of Science in Computer Networks and Security

WinDBG Anti-RootKit Extension

(Python, R, C++) Explainable outlier/anomaly detection through decision tree conditioning

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

Useful Toolbox for Anomaly Detection

H2Oai GPU Edition

Faster and more precisely than Grad-CAM

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.

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

A collection of Poisson lognormal models for multivariate count data analysis

SJTU CS386 Digital Image Processing

A tidyverse suite for (pre-) machine-learning: cluster, PCA, permute, impute, rotate, redundancy, triangular, smart-subset, abundant and variable features.

A toolkit for automated log parsing [ICSE'19, TDSC'18, DSN'16]

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