Codeup repository for anomaly detection exercises

Repositorio para datos y documentos de la asignatura del máster en Ciencia de Datos: Minería de datos, detección de anomalías y aprendizaje no supervisado.

Next-value prediction and Anomaly Detection with Keras on medical data.

This is the technical task by Eilink Digital Research Lab.

Anomaly detection using IF, LOF, OC-SVM, Autoencoder.

Applying anomaly detection methods on Multi-Armed Bandit problems

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

2022 Winter Individual Research

Anomaly Detection in Time Series Data using Autoencoders approach.

This GitHub repository provides a comprehensive set of tools and algorithms for detecting fraud anomalies in various data sources. Fraudulent activities can have severe consequences, impacting businesses and individuals alike. With this repository, we aim to empower researchers with effective techniques to identify and prevent fraudulent behavior.

Time Series Anomaly Detection

Data Science Examples

Autoencoder for gait recognition and elderly monitoring.

Time Series Model Implementation Repository

Graph kernel techniques to create profiles for users in a network and identify anomalous behaviour

ML workflow on HAR dataset

Perform anomaly detection on Bank Marketing dataset

Illegal, unreported, and unregulated (IUU) fishing is a major concern for long term sustainability for the fishing industry and ocean health. By using semi-supervised learning, I developed an Anomaly Detection model that is able to detect IUU activities using loitering events on any given trip for any given vessel, using real-time data

This project was undertaken as part of my work with the Internet Equity Initiative at the Data Science Institute, University of Chicago. More details about the initiative are here http://internetequity.uchicago.edu/about/the-initiative/.