Matevž Kos
Sistemski Inženir Tehnik Corporate Sektor Za Informacijski Sistem
Kranj, Slovenia
Summary
👤
Senior🎓
Top SchoolMatevž Kos is a systems engineer with a decade of hands-on IT experience, currently supporting corporate information systems at ELAN Group after administering networks and servers for educational and private organizations. He blends practical systems administration (Linux/Windows servers, AD, GPO, backups, network and Internet management) with software skills in JavaScript, PHP, Java and C#, and is comfortable with Docker and Git-based workflows. Beyond routine ops, he has contributed backend fixes to the widely used Orange3 data-analysis project, improving stability and preprocessing features by modifying C++ and widget logic. Known for troubleshooting across hardware and software boundaries, he brings a pragmatic, user-focused approach to automating and hardening IT services while mentoring colleagues. Contactable at matevz.kos@hotmail.com for collaboration on IT or programming projects.
10 years of coding experience
3 years of employment as a software developer
Master's degree Computer Technology/Computer Systems Technology, Master's degree Computer Technology/Computer Systems Technology at Tehniški šolski center Kranj
English, slovene
Stackoverflow
1reputation
0reached
0answers
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Github Skills (16)
data-mining10
machine-learning10
python10
data-science10
scikit-learn9
numpy9
classification9
cprogramming-language9
scikit9
c-language9
data-visualization8
data-visualisation8
regression8
pandas8
data-visualizations8
Programming languages (1)
Github contributions (5)
biolab/orange3
Mar 2016 - Aug 2016
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Role in this project:
Back-end Developer
Back-end DeveloperContributions:43 commits, 8 PRs, 16 comments in 5 months
Contributions summary:Matevž primarily focused on fixing issues within the `Orange3` repository, specifically addressing crashes in the rank widget due to missing target class values. They made changes to C++ code within the `Orange/preprocess/_relieff.cpp` file, likely to improve the stability and robustness of the data analysis tools. Additionally, they contributed to enhancing the preprocessor widget by introducing a feature for selecting random features. Further modifications improved auto-apply functionality and corrected the display of numerical values in tables.
data-analysisdata-miningdata-sciencemachine-learningdata-visualization
matevzkren/orange3
Mar 2016 - Aug 2016
Contributions:83 pushes, 10 branches in 5 months
data-miningminingorangesuite
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