Insight-Sogang-Univ/insight-13th
May 2025 – Jun 2025
2 Months active
Languages Used
Jupyter NotebookPythonSQL
Technical Skills
ADF TestAssociation Rule MiningBERTCatBoostClassificationData Analysis
suyeonlee01
PROFILE
Suyeonlee01
Kate Lee developed end-to-end data science workflows for the Insight-Sogang-Univ/insight-13th repository, focusing on practical machine learning and analytics features over two months. She built an employee leave prediction system using ensemble methods and model comparison, and implemented market basket analysis for cross-selling with association rule mining. Her work included deep learning pipelines for MNIST classification and NLP assignments exploring BERT, attention mechanisms, and financial sentiment analysis. In time series analytics, she delivered forecasting pipelines with PyTorch and LSTM, and prepared climate datasets with rigorous preprocessing and stationarity testing. She primarily used Python, PyTorch, Pandas, and Scikit-learn throughout.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
10Total
Bugs
0
Commits
10
Features
7
Lines of code
35,856
Activity Months2
Your Network
1029 people
Work History
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025 (Month: 2025-06) performance summary for Insight-Sogang-Univ/insight-13th. Key features delivered: end-to-end Electricity Consumption Time-Series Forecasting workflow in PyTorch, and Seoul Temperature dataset preparation with stationarity evaluation. Major bugs fixed: none reported this month. Overall impact: established reusable forecasting and data-prep pipelines that enable data-driven energy planning and climate analytics, with clear evaluation metrics and data quality checks. Technologies/skills demonstrated: Python, PyTorch, time-series modeling (LSTM), data preprocessing, Dataset/DataLoader customization, MSE loss training, Adam optimization, correlation metrics, regression scores, and statistical testing.
2 Commits • 2 Features
Jun 1, 2025June 2025 (Month: 2025-06) performance summary for Insight-Sogang-Univ/insight-13th. Key features delivered: end-to-end Electricity Consumption Time-Series Forecasting workflow in PyTorch, and Seoul Temperature dataset preparation with stationarity evaluation. Major bugs fixed: none reported this month. Overall impact: established reusable forecasting and data-prep pipelines that enable data-driven energy planning and climate analytics, with clear evaluation metrics and data quality checks. Technologies/skills demonstrated: Python, PyTorch, time-series modeling (LSTM), data preprocessing, Dataset/DataLoader customization, MSE loss training, Adam optimization, correlation metrics, regression scores, and statistical testing.
June 2025
May 2025
8 Commits • 5 Features
May 1, 2025May 2025 monthly summary focusing on feature-driven analytics and ML education work across Insight-Sogang-Univ/insight-13th. Delivered end-to-end data science workflows, enabling hands-on experimentation and clear business-value artifacts.
May 2025
8 Commits • 5 Features
May 1, 2025May 2025 monthly summary focusing on feature-driven analytics and ML education work across Insight-Sogang-Univ/insight-13th. Delivered end-to-end data science workflows, enabling hands-on experimentation and clear business-value artifacts.
Activity
Loading activity data...
Quality Metrics
Correctness81.0%
Maintainability78.0%
Architecture80.0%
Performance74.0%
AI Usage36.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPythonSQL
Technical Skills
ADF TestARIMAAssociation Rule MiningBERTCatBoostClassificationData AnalysisData CleaningData PreprocessingData VisualizationDeep LearningDifferencingEnsemble MethodsFeature EngineeringGPT
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline