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vc1492a

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Senior Data Scientist @ Terran Orbital Open Source Software Enthusiast

Funding Links: https://github.com/sponsors/vc1492a

GitHub Sponsors Profile

Thanks for coming to my sponsor page!
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.
Become a sponsor by Github donations.
I have great one-time and monthly sponsoring tiers. Pick the one that fits your budget. Your support is greatly appreciated!
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.

Featured Works

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].

Language: Python - Stars: 319
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rafaelkallis rafaelkallis
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