blackSwanCS/Higgs_collaboration_B
Jun 2025 – Jun 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisData Analysis SetupData LoadingData VisualizationMachine LearningMachine Learning Integration
Hennart--Frugone Noe
PROFILE
Hennart--frugone Noe
Noé Hennart-Frugone developed end-to-end enhancements for the blackSwanCS/Higgs_collaboration_B repository, focusing on scalable data ingestion and predictive analytics integration. Using Python and Jupyter Notebook, Noé implemented a workflow that loads data into DataFrames, prepares it for analysis, and embeds predictive models directly into the statistical pipeline. The work expanded the project’s statistical analysis framework, introducing advanced features such as AMS threshold scanning, mu calculations with systematics, and binned likelihoods, all integrated with machine learning components. This approach improved experimental reproducibility and positioned the project for robust, data-driven decision making, demonstrating depth in scientific computing and statistical modeling.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
2
Lines of code
1,781
Activity Months1
Your Network
41 people
Work History
June 2025
13 Commits • 2 Features
Jun 1, 2025June 2025: Delivered end-to-end enhancements to data ingestion and predictive analytics integration and expanded statistical analysis capabilities to support robust data-driven decision making. The work positioned the project for scalable analytics pipelines, improved model integration within the statistical workflow, and stronger experimental reproducibility.
13 Commits • 2 Features
Jun 1, 2025June 2025: Delivered end-to-end enhancements to data ingestion and predictive analytics integration and expanded statistical analysis capabilities to support robust data-driven decision making. The work positioned the project for scalable analytics pipelines, improved model integration within the statistical workflow, and stronger experimental reproducibility.
June 2025
Activity
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Quality Metrics
Correctness77.8%
Maintainability78.4%
Architecture74.6%
Performance64.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AnalysisData Analysis SetupData LoadingData VisualizationMachine LearningMachine Learning IntegrationMatplotlibNumPyNumerical ComputingPythonSciPyScientific ComputingStatistical AnalysisStatistical ModelingiMinuit
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