sejongsmarcle/2025_Junior_ML_Study
Mar 2025 – Mar 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
Data AnalysisData VisualizationDocumentationMachine LearningMatplotlibNumPy
kingsans787
PROFILE
Kingsans787
Contributed to the sejongsmarcle/2025_Junior_ML_Study repository by developing three core features focused on onboarding and hands-on machine learning practice. Built a reproducible workflow for a K-Nearest Neighbors regression model in Python, leveraging NumPy and scikit-learn to predict fish weight from length, including data preparation, model training, and evaluation across different neighbor counts. Authored and iteratively refined a markdown-based personal introduction document, improving clarity and formatting to support team knowledge sharing. Added a reference document for the Week 1 assignment, streamlining access to study materials. Emphasized clear documentation and reproducibility to accelerate onboarding and collaborative learning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
3
Lines of code
330
Activity Months1
Your Network
9 peopleWork History
March 2025
9 Commits • 3 Features
Mar 1, 2025March 2025 monthly summary for sejongsmarcle/2025_Junior_ML_Study: Focused on delivering robust study program artifacts and a hands-on ML experiment, with clear documentation and reproducible workflows to accelerate onboarding and learning.
9 Commits • 3 Features
Mar 1, 2025March 2025 monthly summary for sejongsmarcle/2025_Junior_ML_Study: Focused on delivering robust study program artifacts and a hands-on ML experiment, with clear documentation and reproducible workflows to accelerate onboarding and learning.
March 2025
Activity
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Quality Metrics
Correctness93.2%
Maintainability93.2%
Architecture93.2%
Performance93.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Data AnalysisData VisualizationDocumentationMachine LearningMatplotlibNumPyPythonScikit-learn
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