Chameleon-company/MOP-Code
Nov 2024 – May 2025
3 Months active
Languages Used
Jupyter NotebookPythonCSSHTMLJavaScriptMarkdown
Technical Skills
API IntegrationData CleaningData FetchingData VisualizationPandasPlotly
aniraj2020
PROFILE
Aniraj2020
Over a three-month period, contributed to the Chameleon-company/MOP-Code repository by developing end-to-end data pipelines and analytics dashboards for food security and activity recognition projects. Built a unified AI Flask web application integrating multiple analytics modules, including a Food Security Dashboard with data fetching, cleaning, and visualization features using Python, Flask, and Plotly. Delivered a reproducible deep learning pipeline for activity recognition from wearable sensor data, employing LSTM and GRU models with Keras and TensorFlow. Enhanced project maintainability through improved documentation, standardized folder structures, and deployment readiness, ensuring clear onboarding and reproducibility for future contributors without introducing any reported bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
4
Lines of code
23,721
Activity Months3
Your Network
98 peopleWork History
May 2025
3 Commits • 2 Features
May 1, 2025May 2025 performance summary for Chameleon-company/MOP-Code: Implemented and delivered the UC8 activity recognition submission using wearable sensor data, including data processing pipeline, model training with LSTM/GRU, evaluation scripts, and full documentation. Reorganized project structure and enhanced onboarding with updated README and folder layout. Performed repository hygiene by removing unnecessary artifacts and tightening .gitignore. The work establishes a reproducible baseline for UC8 submission and improves maintainability and handover readiness.
3 Commits • 2 Features
May 1, 2025May 2025 performance summary for Chameleon-company/MOP-Code: Implemented and delivered the UC8 activity recognition submission using wearable sensor data, including data processing pipeline, model training with LSTM/GRU, evaluation scripts, and full documentation. Reorganized project structure and enhanced onboarding with updated README and folder layout. Performed repository hygiene by removing unnecessary artifacts and tightening .gitignore. The work establishes a reproducible baseline for UC8 submission and improves maintainability and handover readiness.
May 2025
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 — Delivered a unified AI Flask web application integrating food security analytics with routes for multiple AI projects (food security, health behavior, traffic analysis, vehicle classification) and a safety perception prediction module. Implemented the comprehensive Food Security Dashboard within the Flask app, including data fetching, preparation, and visualization for food security metrics. Included notebooks and code updates to support visualizations and dependencies, and added a dedicated requirements.txt for reproducibility and deployment readiness.
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 — Delivered a unified AI Flask web application integrating food security analytics with routes for multiple AI projects (food security, health behavior, traffic analysis, vehicle classification) and a safety perception prediction module. Implemented the comprehensive Food Security Dashboard within the Flask app, including data fetching, preparation, and visualization for food security metrics. Included notebooks and code updates to support visualizations and dependencies, and added a dedicated requirements.txt for reproducibility and deployment readiness.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for Chameleon-company/MOP-Code: Delivered end-to-end food security data pipeline and analytics suite using the Melbourne Open Data API. Implemented data fetch, cleaning, analysis, visualization of food insecurity types and demographic distributions, and linear regression-based predictive trends. Added export capability for generated plots and refactored respondent group data for consistency. Prepared knowledge transfer documentation and included a corrected dataset.
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for Chameleon-company/MOP-Code: Delivered end-to-end food security data pipeline and analytics suite using the Melbourne Open Data API. Implemented data fetch, cleaning, analysis, visualization of food insecurity types and demographic distributions, and linear regression-based predictive trends. Added export capability for generated plots and refactored respondent group data for consistency. Prepared knowledge transfer documentation and included a corrected dataset.
November 2024
Activity
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Quality Metrics
Correctness85.8%
Maintainability85.8%
Architecture85.8%
Performance77.2%
AI Usage37.2%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptJupyter NotebookMarkdownPython
Technical Skills
API IntegrationCSSData AnalysisData CleaningData FetchingData PreprocessingData VisualizationDeep LearningDocumentationFlaskFull Stack DevelopmentHTMLJavaScriptKerasMachine Learning
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