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I work in various domains, such as anomaly detection, forecasting, and data mining, and have developed approaches with a strong focus to let them work in real-world applications.
My open-source projects
In my free time, I like to work on my open-source libraries!
PyNomaly leverages Local Outlier Probabilities for anomaly detection from static or streaming data.
If you want more cool features then I need you as a sponsor!
It is very cool to have so many downloads! Love it! but the increasing number of users also increased the number of questions and requests. I now spent many hours in the evenings and weekends answering your questions, and I'm very happy to keep doing that! However, like most of you, I can spend time only once, which leaves me no time anymore for the development of new functionalities. I would love to spend more time developing new (core) functionalities.
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My Google Scholar page
If academic work interests you, see how I am applying data science in the context of the aerospace industry by checking out my Google Scholar profile.
1 sponsor has funded vc1492a’s work.
Featured work
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vc1492a/PyNomaly
Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].
Python 317