KU-BIG/KUBIG_2025_FALL
Jul 2025 – Aug 2025
2 Months active
Languages Used
KoreanPythonJSONJupyter NotebookR
Technical Skills
Data ScienceDeep LearningMachine LearningNatural Language ProcessingNeural NetworksNumPy
SehunLee0
PROFILE
Sehunlee0
Contributed to the KU-BIG/KUBIG_2025_FALL repository by developing a modular deep learning framework and expanding study materials to support onboarding and experimentation. Built a MultiLayerNet architecture with common layers and optimizers, implemented using Python and PyTorch, and delivered coursework notebooks for CNN and MLP models. Enhanced data analysis capabilities through TabPFN-based tooling, including classifier boundary visualization and outlier detection. Managed data assets with CSVs and R notebooks, ensuring reproducibility and accessibility. Maintained project hygiene by removing outdated files and refining directory structure, resulting in a well-organized codebase that accelerates research cycles and supports ongoing deep learning education.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
17Total
Bugs
0
Commits
17
Features
5
Lines of code
49,671
Activity Months2
Your Network
57 peopleShared Repositories
28
seohyeon0508Member
yooncy1122Member
elishaMember
eunseo5703Member
Haeune-JeonMember
Nam SubinMember
hwang10-22Member
전하은Member
Junhee-Park0Member
Work History
August 2025
11 Commits • 4 Features
Aug 1, 2025August 2025 performance summary for KU-BIG/KUBIG_2025_FALL. Key features delivered include a modular Deep Learning Framework (MultiLayerNet) with common DL layers and optimizers, TabPFN-based data analysis tooling, expanded data assets and study materials, and project scaffolding improvements. Major bugs fixed: none reported this month; ongoing stability enhancements and documentation updates. Overall impact: accelerated experimentation cycles, improved reproducibility, and stronger readiness for upcoming research milestones. Technologies/skills demonstrated span deep learning architecture design, modular framework development, TabPFN experimentation and visualization, data engineering (CSV assets), R notebook workflows, and rigorous project hygiene that supports faster, more reliable releases.
11 Commits • 4 Features
Aug 1, 2025August 2025 performance summary for KU-BIG/KUBIG_2025_FALL. Key features delivered include a modular Deep Learning Framework (MultiLayerNet) with common DL layers and optimizers, TabPFN-based data analysis tooling, expanded data assets and study materials, and project scaffolding improvements. Major bugs fixed: none reported this month; ongoing stability enhancements and documentation updates. Overall impact: accelerated experimentation cycles, improved reproducibility, and stronger readiness for upcoming research milestones. Technologies/skills demonstrated span deep learning architecture design, modular framework development, TabPFN experimentation and visualization, data engineering (CSV assets), R notebook workflows, and rigorous project hygiene that supports faster, more reliable releases.
August 2025
July 2025
6 Commits • 1 Features
Jul 1, 2025July 2025 performance summary for KU-BIG/KUBIG_2025_FALL: Delivered updates to the Deep Learning study materials repository, adding new assignments, PDFs, notebooks, and related resources to improve learner onboarding and ongoing study. Performed 6 commits (5 adds, 1 cleanup) across the month, including removal of an outdated ZIP to maintain content hygiene. Result: more up-to-date, accessible materials for the Fall cohort with traceable changes.
July 2025
6 Commits • 1 Features
Jul 1, 2025July 2025 performance summary for KU-BIG/KUBIG_2025_FALL: Delivered updates to the Deep Learning study materials repository, adding new assignments, PDFs, notebooks, and related resources to improve learner onboarding and ongoing study. Performed 6 commits (5 adds, 1 cleanup) across the month, including removal of an outdated ZIP to maintain content hygiene. Result: more up-to-date, accessible materials for the Fall cohort with traceable changes.
Activity
Loading activity data...
Quality Metrics
Correctness88.2%
Maintainability86.6%
Architecture86.6%
Performance85.8%
AI Usage27.2%
Skills & Technologies
Programming Languages
JSONJupyter NotebookKoreanPythonR
Technical Skills
ClassificationConvolutional Neural Networks (CNN)Data AnalysisData AugmentationData EngineeringData ImputationData PreprocessingData ScienceData VisualizationDataset HandlingDeep LearningJupyter NotebookKerasMachine LearningMatplotlib
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline