Insight-Sogang-Univ/insight-13th
May 2025 – Jun 2025
2 Months active
Languages Used
Jupyter NotebookPythonSQL
Technical Skills
Association Rule MiningCatBoostClassificationCollaborative FilteringData AnalysisData Preprocessing
hyunji1122
PROFILE
Hyunji1122
Over a two-month period, contributed to the Insight-Sogang-Univ/insight-13th repository by developing eight features focused on machine learning, time series analysis, and natural language processing. Delivered end-to-end workflows in Python and Jupyter Notebook, including ensemble classification, collaborative filtering, and market basket analysis, as well as Korean text preprocessing using TF-IDF. Implemented time series forecasting with PyTorch LSTM and ARIMA, incorporating STL decomposition and stationarity testing with ADF and KPSS. Emphasized reproducibility and clear documentation, producing notebooks and artifacts suitable for both research and business insights. The work enabled data-driven decision making and scalable analytics for diverse datasets.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
8
Lines of code
66,942
Activity Months2
Your Network
1159 peopleShared Repositories
28
Work History
June 2025
3 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for Insight-Sogang-Univ/insight-13th: Focused on delivering scalable time-series analytics and forecasting capabilities. No major bugs reported this month; changes centered on feature delivery and experimental notebooks to enable data-driven decision making for energy usage and climate data. Impact highlights include enabling end-to-end time-series analysis, production-style forecasting readiness, and exploratory data analysis for additional datasets, with an emphasis on reproducibility and documentation.
3 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for Insight-Sogang-Univ/insight-13th: Focused on delivering scalable time-series analytics and forecasting capabilities. No major bugs reported this month; changes centered on feature delivery and experimental notebooks to enable data-driven decision making for energy usage and climate data. Impact highlights include enabling end-to-end time-series analysis, production-style forecasting readiness, and exploratory data analysis for additional datasets, with an emphasis on reproducibility and documentation.
June 2025
May 2025
10 Commits • 7 Features
May 1, 2025Month 2025-05 — Insight-Sogang-Univ/insight-13th: Delivered a cohesive set of notebooks and experiments spanning ensemble methods, collaborative filtering, market basket analysis, MNIST classification, and Korean NLP preprocessing. Established reproducible workflows, improved model evaluation, and produced artifacts suitable for assignments and business insights. Key outcomes include tuned ensemble experiments with RandomForestClassifier to boost classification accuracy, MNIST MLP achieving ~89% accuracy, collaborative filtering with MAE/MSE/RMSE evaluation, market basket analytics via Apriori/FP-Growth, and TF-IDF based Korean NLP preprocessing. The work delivers tangible business value through better recommendations, insights into basket data, and ready-to-share research artifacts.
May 2025
10 Commits • 7 Features
May 1, 2025Month 2025-05 — Insight-Sogang-Univ/insight-13th: Delivered a cohesive set of notebooks and experiments spanning ensemble methods, collaborative filtering, market basket analysis, MNIST classification, and Korean NLP preprocessing. Established reproducible workflows, improved model evaluation, and produced artifacts suitable for assignments and business insights. Key outcomes include tuned ensemble experiments with RandomForestClassifier to boost classification accuracy, MNIST MLP achieving ~89% accuracy, collaborative filtering with MAE/MSE/RMSE evaluation, market basket analytics via Apriori/FP-Growth, and TF-IDF based Korean NLP preprocessing. The work delivers tangible business value through better recommendations, insights into basket data, and ready-to-share research artifacts.
Activity
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Quality Metrics
Correctness67.6%
Maintainability66.2%
Architecture63.8%
Performance60.0%
AI Usage23.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPythonSQL
Technical Skills
ADF TestARIMA ModelingAssociation Rule MiningCatBoostClassificationCollaborative FilteringData AnalysisData DecompositionData PreprocessingData VisualizationDeep LearningDifferencingEnsemble MethodsExploratory Data AnalysisHyperparameter Tuning
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