arvindkrishna87/STAT390_SP25_CMIL
May 2025 – May 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Computer VisionData ScienceDeep LearningJupyter NotebooksMachine LearningModel Evaluation
Josiah (Jojo) Kim
PROFILE
Josiah (jojo) Kim
Developed and evaluated adaptive pooling window sizes within a ResNet model enhanced by CBAM and class balancing, focusing on improving performance for imbalanced datasets in the arvindkrishna87/STAT390_SP25_CMIL repository. The work involved implementing multiple pooling strategies in Python using Jupyter Notebooks, conducting rigorous experiments, and updating artifacts to ensure reproducibility and traceability. Emphasis was placed on model evaluation and data-driven analysis to inform deployment decisions. No major bugs were reported or fixed during this period, reflecting a focus on feature development and experimental validation. This effort demonstrated depth in computer vision, deep learning, and reproducible research workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
11,050
Activity Months1
Your Network
8 peopleWork History
May 2025
3 Commits • 1 Features
May 1, 2025May 2025 monthly summary for arvindkrishna87/STAT390_SP25_CMIL: Focused feature work delivering an evidence-based evaluation of adaptive pooling window sizes in a ResNet model augmented with CBAM and class balancing. The work included implementation, experimentation, and artifact updates to enable reproducible assessments, setting the stage for data-driven deployment decisions and potential performance gains on imbalanced datasets. No major bugs reported or fixed this month. This effort demonstrates strong capabilities in CNN architectures, experimentation workflow, and rigorous validation.
3 Commits • 1 Features
May 1, 2025May 2025 monthly summary for arvindkrishna87/STAT390_SP25_CMIL: Focused feature work delivering an evidence-based evaluation of adaptive pooling window sizes in a ResNet model augmented with CBAM and class balancing. The work included implementation, experimentation, and artifact updates to enable reproducible assessments, setting the stage for data-driven deployment decisions and potential performance gains on imbalanced datasets. No major bugs reported or fixed this month. This effort demonstrates strong capabilities in CNN architectures, experimentation workflow, and rigorous validation.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness73.4%
Maintainability73.4%
Architecture66.6%
Performance66.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Computer VisionData ScienceDeep LearningJupyter NotebooksMachine LearningModel EvaluationPython
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline