dataforgoodfr/13_democratiser_sobriete
Dec 2025 – Jan 2026
2 Months active
Languages Used
Python
Technical Skills
Data AnalysisMachine LearningModel OptimizationNatural Language ProcessingAPI integrationdata analysis
Edouard Callet
PROFILE
Edouard Callet
Developed and deployed end-to-end policy recommendation and taxonomy extraction pipelines for the dataforgoodfr/13_democratiser_sobriete repository, focusing on research paper analysis and structured policy data generation. Leveraged Python and machine learning techniques, including model training, optimization, and natural language processing, to automate extraction and classification of policy conclusions with an average accuracy of 86.93%. Integrated a cross-encoder for semantic similarity evaluation and introduced a classification model to categorize policy data by geography and domain. Emphasized reproducibility and maintainability through version-controlled workflows, robust data loading, and structured JSON outputs, accelerating policy analytics and supporting decision-making from unstructured document sources.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
14,223
Activity Months2
Your Network
11 peopleShared Repositories
11
etienneguevelMember
François BONIFACEMember
JesshuanMember
Max BarbetMember
MNIKIEMAMember
Olivier JayletMember
unknownMember
Paul GabrielMember
RegisMember
Work History
January 2026
2 Commits • 1 Features
Jan 1, 2026Month: 2026-01 Focused on building a scalable policy extraction pipeline with taxonomy classification. Delivered an end-to-end pipeline that performs text cleaning, model training, and automated extraction to produce structured JSON outputs. Introduced a classifier to enhance policy data extraction and categorization by geography and policy domain. Also refined data loading paths and model configurations to improve robustness, accuracy, and maintainability. No major bugs reported this month; minor refinements implemented for path handling and configuration stability. Overall impact: accelerates policy data processing for analytics and decision-support, enabling faster and more reliable insights from policy documents. Technologies demonstrated include Python-based NLP pipeline, machine learning classification, JSON schema outputs, and version-controlled workflows.
2 Commits • 1 Features
Jan 1, 2026Month: 2026-01 Focused on building a scalable policy extraction pipeline with taxonomy classification. Delivered an end-to-end pipeline that performs text cleaning, model training, and automated extraction to produce structured JSON outputs. Introduced a classifier to enhance policy data extraction and categorization by geography and policy domain. Also refined data loading paths and model configurations to improve robustness, accuracy, and maintainability. No major bugs reported this month; minor refinements implemented for path handling and configuration stability. Overall impact: accelerates policy data processing for analytics and decision-support, enabling faster and more reliable insights from policy documents. Technologies demonstrated include Python-based NLP pipeline, machine learning classification, JSON schema outputs, and version-controlled workflows.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Focused on delivering an end-to-end policy recommendation extraction capability for research papers, with Version 1 deployed for evaluation in dataforgoodfr/13_democratiser_sobriete. Key results include an average extraction accuracy of 86.93% and a reproducible pipeline from data loading to optimization.
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Focused on delivering an end-to-end policy recommendation extraction capability for research papers, with Version 1 deployed for evaluation in dataforgoodfr/13_democratiser_sobriete. Key results include an average extraction accuracy of 86.93% and a reproducible pipeline from data loading to optimization.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage73.4%
Skills & Technologies
Programming Languages
Python
Technical Skills
API integrationData AnalysisMachine LearningModel OptimizationNatural Language Processingdata analysisdata extractionmachine learningmodel trainingnatural language processing
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