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Namddu

PROFILE

Namddu

Over a two-month period, contributed to the halley1116/2025_DA_study repository by delivering core enhancements and new features focused on data science and machine learning workflows. Developed and integrated sentiment analysis pipelines using Python, Pandas, and Scikit-learn, incorporating LDA topic modeling and improved classifier selection for social media data. Enhanced project structure through repository cleanup, merge conflict resolution, and the addition of testing scaffolding to support maintainability. Improved data visualization and documentation within Jupyter Notebooks, enabling clearer insights and onboarding. Addressed data preprocessing, feature engineering, and exploratory analysis, resulting in more robust, maintainable, and collaborative data analysis processes.

Overall Statistics

Feature vs Bugs

65%Features

Repository Contributions

74Total
Bugs
6
Commits
74
Features
11
Lines of code
53,273
Activity Months2

Work History

February 2025

15 Commits • 4 Features

Feb 1, 2025

February 2025: Delivered key enhancements to the ChatGPT sentiment analysis study, including a sentiment analysis pipeline with LDA topic modeling, improved classifier selection, and enhanced notebook visualizations and documentation. Addressed stopword handling issues, performed notebook maintenance, and introduced an exploratory notebook for student performance data—driving clearer insights, better model accuracy, and improved maintainability.

January 2025

59 Commits • 7 Features

Jan 1, 2025

Month summary for 2025-01: Delivered substantial LYS_2 core enhancements with comprehensive integration across the repository, initiated LYS_24 core expansion groundwork, and implemented core LYS_2 features with ongoing mainline merges. Established testing scaffolding and initial project file uploads to support quality and onboarding. Reconciled merge conflicts and removed obsolete directories, reducing technical debt. Minor path handling fix improves reliability. Overall, the work strengthens core capabilities, accelerates feature delivery, and improves testability and maintainability with a clearer project structure.

Activity

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Quality Metrics

Correctness79.2%
Maintainability79.8%
Architecture74.4%
Performance73.8%
AI Usage22.4%

Skills & Technologies

Programming Languages

JSONJupyter NotebookMarkdownPythonSQLipynb

Technical Skills

AI Integration for LearningBase64 EncodingBasic PythonChi-squared testCleanupCode CleanupCorrelation AnalysisCustomer Churn PredictionData AnalysisData CleaningData ExplorationData LoadingData MergingData PreprocessingData Scaling

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

halley1116/2025_DA_study

Jan 2025 Feb 2025
2 Months active

Languages Used

JSONJupyter NotebookMarkdownPythonSQLipynb

Technical Skills

AI Integration for LearningBasic PythonChi-squared testCleanupCode CleanupCorrelation Analysis