Chameleon-company/MOP-Code
May 2025 – May 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data CleaningData VisualizationDeep LearningExploratory Data Analysis (EDA)Feature EngineeringKeras
Nauman Abid
PROFILE
Nauman Abid
During May 2025, Abid Nauman developed a pedestrian traffic forecasting workflow for the Chameleon-company/MOP-Code repository. He designed and implemented a data pipeline in Python and Jupyter Notebook, focusing on data loading, cleaning, exploratory analysis, and time-based feature engineering using Pandas and NumPy. Abid established a reproducible train/test split and normalized sequential data to prepare inputs for a GRU-based deep learning model built with Keras and TensorFlow. His work addressed the challenge of forecasting pedestrian counts by ensuring clean, well-structured data and a robust modeling foundation. The project demonstrated depth in data preparation and initial model prototyping, with no bugs reported.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
3,358
Activity Months1
Your Network
98 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on business value and technical achievements for the Chameleon-company/MOP-Code project. Highlights include delivered data preparation workflow and an initial GRU-based pedestrian traffic forecasting model, with a clean data pipeline and reproducible train/test split. No major bugs reported this period.
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on business value and technical achievements for the Chameleon-company/MOP-Code project. Highlights include delivered data preparation workflow and an initial GRU-based pedestrian traffic forecasting model, with a clean data pipeline and reproducible train/test split. No major bugs reported this period.
May 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data CleaningData VisualizationDeep LearningExploratory Data Analysis (EDA)Feature EngineeringKerasMachine LearningMatplotlibNumPyPandasScikit-learnTensorFlowTime Series Analysis
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