Develop and Assess Unsupervised Anomaly Detection Methods
This project was completed as a intern opportunity with HPCC Systems in 2019. Curious about projects we are offering for future internships? Take a look at our Ideas List.Â
Find out about the HPCC Systems Summer Internship Program.
Project Description
Create an ECL Bundle encompassing several widely used Anomaly Detection algorithms. Identify at least one algorithm that is parallelizable and implement efficiently in ECL:
Identify a publicly available dataset and method for assessing anomalies in the data
Research state of the art Anomaly Detection algorithms and choose two or more for implementation
Implement methods in ECL on HPCC Systems cluster, and assess results in identifying target anomalies.
By the mid term review we would expect you to have:
To have implemented atelast one algorithm and tested it.
Mentor | Roger Dev Backup Mentor:Â TBD |
Skills needed |
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