Insight-Sogang-Univ/insight-13th
May 2025 – Jun 2025
2 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
ADF TestBERTBag of Words (BoW)Collaborative FilteringCountVectorizerData Analysis
Minhui21
PROFILE
Minhui21
Minhui Kim contributed to the Insight-Sogang-Univ/insight-13th repository by developing end-to-end machine learning and deep learning solutions across multiple domains. They built an XGBoost-based employee attrition prediction pipeline, implemented collaborative filtering for group recommendations, and conducted NLP experiments using BERT and GPT. For time series forecasting, Minhui engineered RNN and LSTM models to predict electricity consumption and analyzed historical temperature data for Seoul, applying statistical tests and decomposition techniques. Their work emphasized reproducibility and robust data pipelines, leveraging Python, PyTorch, and Pandas. Over two months, Minhui delivered eight features, demonstrating depth in model development, evaluation, and data engineering.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
8
Lines of code
30,765
Activity Months2
Your Network
28 people
Work History
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for Insight-Sogang-Univ/insight-13th: Two time-series feature deliverables were advanced, delivering business-ready forecasting capabilities and enriched data analysis context. No major bugs were reported within the scope of this period.
2 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for Insight-Sogang-Univ/insight-13th: Two time-series feature deliverables were advanced, delivering business-ready forecasting capabilities and enriched data analysis context. No major bugs were reported within the scope of this period.
June 2025
May 2025
9 Commits • 6 Features
May 1, 2025May 2025 performance summary for Insight-Sogang-Univ/insight-13th: Key features delivered, improvements, and experiments spanned ML modeling, data engineering, recommendations, DL, NLP, and time series. The work focused on delivering business value through predictive insights, reproducible experiments, and robust pipelines across domains.
May 2025
9 Commits • 6 Features
May 1, 2025May 2025 performance summary for Insight-Sogang-Univ/insight-13th: Key features delivered, improvements, and experiments spanned ML modeling, data engineering, recommendations, DL, NLP, and time series. The work focused on delivering business value through predictive insights, reproducible experiments, and robust pipelines across domains.
Activity
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Quality Metrics
Correctness75.4%
Maintainability74.6%
Architecture71.0%
Performance67.2%
AI Usage34.6%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
ADF TestARIMA ModelingBERTBag of Words (BoW)Collaborative FilteringCountVectorizerData AnalysisData DecompositionData PreprocessingDeep LearningDifferencingFeature EngineeringGPTHugging Face TransformersImage Classification
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