kietmcaproject/AI_AI101B_2024-25
Apr 2025 – May 2025
2 Months active
Languages Used
Python
Technical Skills
Data AnalysisData VisualizationMachine LearningMatplotlibNumPyPandas
imran-988
PROFILE
Imran-988
Developed core AI features in the kietmcaproject/AI_AI101B_2024-25 repository, focusing on student performance prediction and emotion detection projects. Built end-to-end Jupyter notebook workflows for data analysis and machine learning, including data loading, preprocessing, visualization, and initial modeling with Linear Regression and Naive Bayes. Consolidated project assets and documentation to support reproducibility and stakeholder engagement, organizing materials such as PDFs, notebooks, and presentations for efficient onboarding. Leveraged Python, Pandas, and Scikit-learn to implement data-driven solutions, with an emphasis on clear commit history and reproducible artifacts. Prioritized documentation and knowledge transfer, with no major bugs reported during the period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
10,386
Activity Months2
Your Network
140 peopleWork History
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for the AI_AI101B_2024-25 project. Focused on consolidating knowledge assets and ensuring project readiness through comprehensive documentation and materials for AI Emotion Detection. No major bug fixes completed this month; efforts prioritized documentation, asset curation, and stakeholder-ready deliverables.
1 Commits • 1 Features
May 1, 2025May 2025 monthly summary for the AI_AI101B_2024-25 project. Focused on consolidating knowledge assets and ensuring project readiness through comprehensive documentation and materials for AI Emotion Detection. No major bug fixes completed this month; efforts prioritized documentation, asset curation, and stakeholder-ready deliverables.
May 2025
April 2025
4 Commits • 2 Features
Apr 1, 2025For 2025-04, delivered core AI project work in kietmcaproject/AI_AI101B_2024-25, focusing on data-driven student performance prediction and deliverables. Implemented an end-to-end notebook workflow for predicting student performance using Linear Regression, including data loading, preprocessing, and visualization, plus initial modeling scaffolding. Produced AI project deliverables and documentation (MSE2 materials) with a main document, synopsis, and a Naive Bayes-based email spam classifier presentation. All work is tracked via clear commits, establishing reproducible artifacts. No major bugs reported this month. Impact includes faster stakeholder feedback cycles and a solid base for future model improvements.
April 2025
4 Commits • 2 Features
Apr 1, 2025For 2025-04, delivered core AI project work in kietmcaproject/AI_AI101B_2024-25, focusing on data-driven student performance prediction and deliverables. Implemented an end-to-end notebook workflow for predicting student performance using Linear Regression, including data loading, preprocessing, and visualization, plus initial modeling scaffolding. Produced AI project deliverables and documentation (MSE2 materials) with a main document, synopsis, and a Naive Bayes-based email spam classifier presentation. All work is tracked via clear commits, establishing reproducible artifacts. No major bugs reported this month. Impact includes faster stakeholder feedback cycles and a solid base for future model improvements.
Activity
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Quality Metrics
Correctness88.0%
Maintainability80.0%
Architecture80.0%
Performance84.0%
AI Usage28.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData VisualizationMachine LearningMatplotlibNumPyPandasPythonScikit-learnSeaborn
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