Algorithms for the R environment that are able to detect high-density anomalies. Such anomalies are deviant cases positioned in the most normal regions of the data space.

Anomaly/outlier detection using Isolation forest

This notebook gives an example for an auto-encoder trained on UCSD Anomaly Detection Dataset

One-class classification approach using error of image transformation into one image

Here I am starting with Machine Learning notes after SQL notes. I have covered the following topics such as:

A Stock Anomaly detection is a project for learning the detection of abnormal instances, called anomalies (or outliers) in the stock market. You’ll design a warning system that will alert regulators of stock price manipulation. This project has applications in data cleaning and detecting fraud.

An official source code for paper "Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning", accepted by ACM MM 2023.

Implementation of the method of detecting anomalies in relation database user behavior based on the assessment of SQL-queries’ results

Official implementation of our research paper. DOI: 10.1109/JIOT.2024.3360882

Anomaly detection from ships' Automatic Identification System (AIS) data

Use z-score analysis to find out anomalous behavior in the room by analyzing the condition of the light in your room.

OCR to detect and recognize dot-matrix text written with inkjet-printed on medical PVC bag

an end to end anomaly intrusion base on deep learn

This project focuses on network anomaly detection due to the exponential growth of network traffic and the rise of various anomalies such as cyber attacks, network failures, and hardware malfunctions. This project implement clustering algorithms from scratch, including K-means, Spectral Clustering, Hierarchical Clustering, and DBSCAN

Nonnegative-Constrained Joint Collaborative Representation With Union Dictionary for Hyperspectral Anomaly Detection

ML Mini-Projects, in the context of Andrew's Ng coursera course. Implemented in Octave.

This repository is showcasing our Anomaly Detection System, developed as our final project in the software engineering course, utilizing basic statistical techniques like mean, variance, and covariance to detects anomalies

Seasonal ESD is an anomaly detection algorithm implemented at Twitter: https://arxiv.org/pdf/1704.07706.pdf