blackSwanCS/Higgs_collaboration_B
Jun 2025 – Jun 2025
1 Month active
Languages Used
Python
Technical Skills
Code CleanupData AnalysisMachine LearningScientific ComputingStatistical Modeling
Vandier Louis-Marie
PROFILE
Vandier Louis-marie
During June 2025, Louis-Marie Vandier overhauled the statistical analysis framework in the blackSwanCS/Higgs_collaboration_B repository, focusing on more accurate AMS calculations and robust threshold optimization. Leveraging Python and skills in scientific computing and statistical modeling, he consolidated updates to the statistical_analysis modules, integrated workflows for Tasks 1B and 2_b, and introduced refined gatekeeping for Task 1A. His work stabilized data binning and improved holdout processing, reducing evaluation errors and edge-case failures. Through targeted code cleanup and enhancements, Louis-Marie improved the maintainability and reliability of the analytics pipeline, enabling faster feedback loops for model evaluation and threshold tuning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
1
Lines of code
264
Activity Months1
Your Network
41 people
Work History
June 2025
11 Commits • 1 Features
Jun 1, 2025June 2025 performance summary for blackSwanCS/Higgs_collaboration_B. This period centered on a substantial overhaul of the statistical analysis framework to enable more accurate AMS calculations, robust threshold optimization, and integration of 1B/2_b tasks, while gating Task 1A and stabilizing data binning. The work enhances evaluation reliability, accelerates feedback loops for model tuning, and improves maintainability of analytics components.
11 Commits • 1 Features
Jun 1, 2025June 2025 performance summary for blackSwanCS/Higgs_collaboration_B. This period centered on a substantial overhaul of the statistical analysis framework to enable more accurate AMS calculations, robust threshold optimization, and integration of 1B/2_b tasks, while gating Task 1A and stabilizing data binning. The work enhances evaluation reliability, accelerates feedback loops for model tuning, and improves maintainability of analytics components.
June 2025
Activity
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Quality Metrics
Correctness76.4%
Maintainability78.2%
Architecture71.0%
Performance65.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Code CleanupData AnalysisMachine LearningScientific ComputingStatistical Modeling
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