dataforgoodfr/13_reveler_inegalites_cinema
Mar 2025 – Apr 2025
2 Months active
Languages Used
PythonBashDockerfileText
Technical Skills
Code RefactoringPEP8 CompliancePre-commit HooksBash ScriptingBatch ProcessingBuild Process
Audrey Duran
PROFILE
Audrey Duran
Worked on the dataforgoodfr/13_reveler_inegalites_cinema repository to enhance machine learning image workflows by developing a CSV-driven batch processing pipeline for analyzing film data and integrating updated classifier models. Focused on deployment readiness, the work included creating a Dockerfile for containerization and stabilizing dependencies through requirements management and import fixes. Addressed code quality by refactoring Python scripts for PEP8 compliance, resolving pre-commit hook failures, and improving maintainability. Leveraged Python, Bash scripting, and Docker to streamline the build process, ensure reproducible deployments, and support ongoing maintenance, resulting in a more robust and scalable machine learning image analysis pipeline.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
7Total
Bugs
1
Commits
7
Features
2
Lines of code
1,023
Activity Months2
Your Network
12 peopleShared Repositories
12
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Florian_YunMember
hadrien PoinseauxMember
ndretexMember
Julien-CommesMember
LudivineLacourMember
Nicolas RevelMember
Paul GabrielMember
lina kaciMember
Work History
April 2025
6 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for dataforgoodfr/13_reveler_inegalites_cinema. Focused on delivering scalable ML-image capabilities and ensuring deployment readiness through containerization and dependency maintenance. The work enabled batch processing of film data, integration of updated classifier models, and a robust packaging setup to support reliable rollout and ongoing maintenance.
6 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for dataforgoodfr/13_reveler_inegalites_cinema. Focused on delivering scalable ML-image capabilities and ensuring deployment readiness through containerization and dependency maintenance. The work enabled batch processing of film data, integration of updated classifier models, and a robust packaging setup to support reliable rollout and ongoing maintenance.
April 2025
March 2025
1 Commits
Mar 1, 2025March 2025 summary for dataforgoodfr/13_reveler_inegalites_cinema: Focused on code quality improvements and CI stability for the ML image pipeline. Fixed PEP8 issues, resolved pre-commit hook failures, and streamlined imports and variable assignments to improve maintainability and reliability of ML code.
March 2025
1 Commits
Mar 1, 2025March 2025 summary for dataforgoodfr/13_reveler_inegalites_cinema: Focused on code quality improvements and CI stability for the ML image pipeline. Fixed PEP8 issues, resolved pre-commit hook failures, and streamlined imports and variable assignments to improve maintainability and reliability of ML code.
Activity
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Quality Metrics
Correctness85.6%
Maintainability85.8%
Architecture74.4%
Performance67.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashDockerfilePythonText
Technical Skills
Bash ScriptingBatch ProcessingBuild ProcessCode RefactoringComputer VisionData ProcessingDeep LearningDependency ManagementDockerFile HandlingMachine LearningModel DeploymentPEP8 CompliancePre-commit HooksPython
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline