HUFS-DAT/2024-2_Seminar
Nov 2024 – Nov 2024
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
ClusteringDBSCANData VisualizationDimensionality ReductionK-MeansMachine Learning
seosumin0123
PROFILE
Seosumin0123
Eileen developed an end-to-end analytics workflow for the HUFS-DAT/2024-2_Seminar repository, focusing on Fashion-MNIST data exploration and clustering. She implemented a comprehensive suite that integrates data visualization and clustering techniques, including PCA, t-SNE, DBSCAN, and K-Means, with an added elbow method to optimize cluster selection. Using Python, Pandas, and Scikit-learn within Jupyter Notebook, Eileen enabled users to perform rapid exploratory analysis and generate actionable insights from high-dimensional data. Her work established a consistent, reproducible process for model-informed decision making. The feature was delivered as a traceable, initial iteration, demonstrating depth in both workflow design and technical execution.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
2,147
Activity Months1
Your Network
1007 people
Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for HUFS-DAT/2024-2_Seminar focused on delivering an end-to-end Fashion-MNIST analytics workflow. Key feature delivery and technical achievements were completed within the month, enabling rapid data exploration and model-informed decision making.
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for HUFS-DAT/2024-2_Seminar focused on delivering an end-to-end Fashion-MNIST analytics workflow. Key feature delivery and technical achievements were completed within the month, enabling rapid data exploration and model-informed decision making.
November 2024
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
ClusteringDBSCANData VisualizationDimensionality ReductionK-MeansMachine LearningMatplotlibPCAPandasPythonScikit-learnt-SNE
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