OpenHUTB/nn
Apr 2026 – May 2026
2 Months active
Languages Used
Python
Technical Skills
Computer VisionDeep LearningMachine LearningPyTorchdata augmentationdata science
9851zzz
PROFILE
9851zzz
Worked on the OpenHUTB/nn repository to enhance convolutional neural network (CNN) training for MNIST digit recognition using Python and PyTorch. Focused on improving model performance and training efficiency through GPU acceleration, data augmentation, and architecture refinements. Addressed deprecated API usage to ensure compatibility with current PyTorch versions and improved code maintainability by expanding documentation and adding Chinese annotations. Strengthened test reliability by renaming functions to avoid pytest conflicts, supporting smoother CI integration. The work emphasized reproducibility, rapid experimentation, and onboarding for new contributors, demonstrating depth in computer vision, deep learning, and model evaluation within a collaborative development environment.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
2
Lines of code
659
Activity Months2
Your Network
263 peopleWork History
May 2026
1 Commits • 1 Features
May 1, 2026May 2026 monthly summary for OpenHUTB/nn: Delivered key performance and reliability improvements to the MNIST CNN training workflow, enhanced API compatibility with PyTorch, and strengthened documentation and test stability. The work reduces time-to-iterate on MNIST experiments, improves final model accuracy, and mitigates risks from deprecated APIs and pytest conflicts. Demonstrated strong skills in PyTorch CNN optimization, Python maintenance, API modernization, and clear multi-language documentation to boost developer productivity and product reliability.
1 Commits • 1 Features
May 1, 2026May 2026 monthly summary for OpenHUTB/nn: Delivered key performance and reliability improvements to the MNIST CNN training workflow, enhanced API compatibility with PyTorch, and strengthened documentation and test stability. The work reduces time-to-iterate on MNIST experiments, improves final model accuracy, and mitigates risks from deprecated APIs and pytest conflicts. Demonstrated strong skills in PyTorch CNN optimization, Python maintenance, API modernization, and clear multi-language documentation to boost developer productivity and product reliability.
May 2026
April 2026
6 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for OpenHUTB/nn focused on CNN MNIST digit recognition improvements and code maintenance. Delivered GPU-accelerated training, data augmentation, and architecture refinements to boost recognition performance and training efficiency. Addressed API compatibility with PyTorch, expanded tests, and improved documentation to ensure reliability, reproducibility, and smoother onboarding for new contributors. The work lays a solid foundation for rapid experimentation and scalable deployment.
April 2026
6 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for OpenHUTB/nn focused on CNN MNIST digit recognition improvements and code maintenance. Delivered GPU-accelerated training, data augmentation, and architecture refinements to boost recognition performance and training efficiency. Addressed API compatibility with PyTorch, expanded tests, and improved documentation to ensure reliability, reproducibility, and smoother onboarding for new contributors. The work lays a solid foundation for rapid experimentation and scalable deployment.
Activity
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Quality Metrics
Correctness83.0%
Maintainability80.0%
Architecture83.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Computer VisionData ScienceDeep LearningMachine LearningPyTorchdata augmentationdata sciencedeep learningmachine learningmodel evaluation
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