Chameleon-company/MOP-Code
Dec 2024 – Mar 2025
3 Months active
Languages Used
CSSHTMLPythonJavaScript
Technical Skills
Data VisualizationFlaskMatplotlibPandasWeb DevelopmentCSS
ESHA NAGI
PROFILE
Esha Nagi
Eshan Agi developed core features for the Chameleon-company/MOP-Code repository over three months, focusing on interactive data dashboards and AI project scaffolding. He built a Flask-based web dashboard for visualizing physical activity, enabling dynamic data loading, gender-based filtering, and exploratory plotting using Python, Pandas, and Matplotlib. Eshan enhanced the user interface with accessible theming and dark mode, applying CSS and JavaScript to improve usability and maintainability. He also established the foundational structure for a dietary monitoring and nutrition AI project, migrating preprocessing workflows from Colab and documenting the setup. His work emphasized scalable architecture and reproducible, collaborative development practices.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
1,493
Activity Months3
Your Network
98 people
Work History
March 2025
2 Commits • 1 Features
Mar 1, 20252025-03 monthly summary for repository Chameleon-company/MOP-Code: Delivered foundational scaffolding for the Dietary Monitoring and Nutrition AI project, including basic folder structure, placeholders for model training and preprocessing notebooks, and a README to guide future development. Implemented a working preprocessing notebook migrated from Colab to accelerate experimentation and onboarding. No major bugs reported this period. Overall, the work establishes a reproducible foundation for rapid AI model development in nutrition, enabling faster prototyping and clearer collaboration. Technologies demonstrated include Python/Jupyter notebooks, Colab workflow, and robust project documentation and Git versioning.
2 Commits • 1 Features
Mar 1, 20252025-03 monthly summary for repository Chameleon-company/MOP-Code: Delivered foundational scaffolding for the Dietary Monitoring and Nutrition AI project, including basic folder structure, placeholders for model training and preprocessing notebooks, and a README to guide future development. Implemented a working preprocessing notebook migrated from Colab to accelerate experimentation and onboarding. No major bugs reported this period. Overall, the work establishes a reproducible foundation for rapid AI model development in nutrition, enabling faster prototyping and clearer collaboration. Technologies demonstrated include Python/Jupyter notebooks, Colab workflow, and robust project documentation and Git versioning.
March 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for the Chameleon-company/MOP-Code repository. Focused on delivering user-facing UI improvements with a strong emphasis on accessibility and theming, while maintaining stability in the codebase.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for the Chameleon-company/MOP-Code repository. Focused on delivering user-facing UI improvements with a strong emphasis on accessibility and theming, while maintaining stability in the codebase.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 performance summary for Chameleon-company/MOP-Code. Delivered the foundational Interactive Flask Web Dashboard for Visualizing Physical Activity, enabling loading of activity data, gender-based filtering, and dynamic plots for exploratory analysis. Established project scaffolding, dataset integration, and a scalable codebase. No major production bugs reported this month; QA and refinement will continue in January. Business impact: provides a reusable analytics UI to explore activity trends and support data-driven decisions.
1 Commits • 1 Features
Dec 1, 2024December 2024 performance summary for Chameleon-company/MOP-Code. Delivered the foundational Interactive Flask Web Dashboard for Visualizing Physical Activity, enabling loading of activity data, gender-based filtering, and dynamic plots for exploratory analysis. Established project scaffolding, dataset integration, and a scalable codebase. No major production bugs reported this month; QA and refinement will continue in January. Business impact: provides a reusable analytics UI to explore activity trends and support data-driven decisions.
December 2024
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptPython
Technical Skills
AICSSData PreprocessingData VisualizationFlaskFull Stack DevelopmentJavaScriptMachine LearningMatplotlibPandasProject InitializationPythonWeb Development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline