mauricioantelis/TC1002S
Mar 2025 – Mar 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Accuracy ScoreClassificationConfusion MatrixData AnalysisData PreprocessingData Science
Dhali
PROFILE
Dhali
Contributed to the mauricioantelis/TC1002S repository by restructuring data assets and developing targeted Jupyter notebooks for machine learning education. Focused on organizing student information files to enhance data governance and project maintainability, while also creating notebooks that guide users through Iris dataset exploration, preprocessing, and supervised classification tasks. Leveraged Python, Pandas, and Scikit-learn to implement workflows that support reproducible experiments and clear data visualization. Emphasized disciplined version control with explicit commit messages, resulting in a clearer project structure and improved onboarding for new users. The work prioritized educational value and practical application of supervised learning techniques without addressing bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
25,057
Activity Months1
Your Network
29 peopleWork History
March 2025
4 Commits • 2 Features
Mar 1, 2025March 2025 performance summary for the mauricioantelis/TC1002S repository. Key accomplishments include restructuring and organizing data assets to improve maintainability and educational value, along with the creation of targeted notebooks for Iris data exploration and ML classification. There were no major bugs fixed in this period. Overall impact includes improved data governance, clearer project structure, and practical ML educational tooling that supports faster onboarding and reproducible experiments. Technologies and skills demonstrated include Python notebooks, data visualization, preprocessing, supervised learning workflows, and disciplined Git version control with explicit commit messages.
4 Commits • 2 Features
Mar 1, 2025March 2025 performance summary for the mauricioantelis/TC1002S repository. Key accomplishments include restructuring and organizing data assets to improve maintainability and educational value, along with the creation of targeted notebooks for Iris data exploration and ML classification. There were no major bugs fixed in this period. Overall impact includes improved data governance, clearer project structure, and practical ML educational tooling that supports faster onboarding and reproducible experiments. Technologies and skills demonstrated include Python notebooks, data visualization, preprocessing, supervised learning workflows, and disciplined Git version control with explicit commit messages.
March 2025
Activity
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Quality Metrics
Correctness95.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Accuracy ScoreClassificationConfusion MatrixData AnalysisData PreprocessingData ScienceData VisualizationFile ManagementJupyter NotebookLogistic RegressionMachine LearningMatplotlibModel EvaluationNumPyPandas
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline