Insight-Sogang-Univ/insight-13th
May 2025 – May 2025
1 Month active
Languages Used
Jupyter NotebookPythonSQL
Technical Skills
Association Rule MiningBERTBag of WordsCatBoostClassificationCollaborative Filtering
55eona
PROFILE
55eona
In May 2025, Samoon contributed to the Insight-Sogang-Univ/insight-13th repository by developing three core features focused on HR analytics, customer recommendations, and deep learning experimentation. He built an Employee Leave Prediction Model using Python and scikit-learn, implementing data pipelines, preprocessing, and classifier evaluation to forecast attrition risk. For customer analytics, he applied collaborative filtering and association rule mining to deliver personalized recommendations and identify cross-sell opportunities. Additionally, Samoon consolidated deep learning and NLP experiments, including MNIST classifiers and BERT-based sentiment analysis, producing reusable artifacts and documentation. His work demonstrated strong technical depth and supported future project scalability.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
3
Lines of code
25,525
Activity Months1
Your Network
28 people
Work History
May 2025
7 Commits • 3 Features
May 1, 2025May 2025 Monthly Summary — Insight-Sogang-Univ/insight-13th Summary: In May 2025, delivered three strategic capabilities in Insight-Sogang-Univ/insight-13th: 1) HR attrition risk forecasting via an Employee Leave Prediction Model, including data loading, preprocessing, and evaluation of multiple classifiers with hyperparameter tuning; 2) Customer analytics featuring an item-based/user-based recommendation system and market basket analysis to drive personalized offers and cross-sell opportunities; 3) DL/NLP project consolidation with MNIST experiments, NLP pipelines (Bag of Words/Word2Vec) and BERT/GPT-based sentiment analysis for financial news, with reusable artifacts. No major bugs reported; debugging activities focused on data pipelines and model integration. The work delivered measurable business value: improved staffing planning, targeted recommendations, and richer experimentation documentation. Technologies demonstrated include Python, scikit-learn, collaborative filtering, Apriori/FP-Growth, MNIST DL, NLP (Word2Vec, BERT/GPT), data visualization.
7 Commits • 3 Features
May 1, 2025May 2025 Monthly Summary — Insight-Sogang-Univ/insight-13th Summary: In May 2025, delivered three strategic capabilities in Insight-Sogang-Univ/insight-13th: 1) HR attrition risk forecasting via an Employee Leave Prediction Model, including data loading, preprocessing, and evaluation of multiple classifiers with hyperparameter tuning; 2) Customer analytics featuring an item-based/user-based recommendation system and market basket analysis to drive personalized offers and cross-sell opportunities; 3) DL/NLP project consolidation with MNIST experiments, NLP pipelines (Bag of Words/Word2Vec) and BERT/GPT-based sentiment analysis for financial news, with reusable artifacts. No major bugs reported; debugging activities focused on data pipelines and model integration. The work delivered measurable business value: improved staffing planning, targeted recommendations, and richer experimentation documentation. Technologies demonstrated include Python, scikit-learn, collaborative filtering, Apriori/FP-Growth, MNIST DL, NLP (Word2Vec, BERT/GPT), data visualization.
May 2025
Activity
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Quality Metrics
Correctness81.4%
Maintainability77.2%
Architecture78.6%
Performance67.2%
AI Usage41.4%
Skills & Technologies
Programming Languages
Jupyter NotebookPythonSQL
Technical Skills
Association Rule MiningBERTBag of WordsCatBoostClassificationCollaborative FilteringData AnalysisData PreprocessingData VisualizationDeep LearningEnsemble MethodsFeature EngineeringGPTLangchainLightGBM
Repositories Contributed To
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