Solvro/ml-wakacyjne-wyzwanie-2025
Aug 2025 – Aug 2025
1 Month active
Languages Used
Python
Technical Skills
Convolutional Neural Networks (CNNs)Data Loading and PreprocessingDeep LearningJupyter NotebooksModel Training and EvaluationNeural Networks
Karolina Nowacka
PROFILE
Karolina Nowacka
Contributed to the Solvro/ml-wakacyjne-wyzwanie-2025 repository by developing two PyTorch-based Jupyter notebooks designed to accelerate onboarding and practical machine learning training for internal developers. The work focused on building educational assets that cover both theoretical and hands-on aspects of neural networks and computer vision, including topics such as tensors, neural network layers, activation functions, loss functions, and model evaluation. Leveraging Python and PyTorch, the notebooks provide a reproducible setup for model training and data preprocessing, culminating in a practical assignment involving convolutional neural networks for handwritten digit classification. No bugs were reported, reflecting a focus on foundational feature delivery.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,394
Activity Months1
Your Network
5 peopleSame Organization
@student.pwr.edu.pl2
Shared Repositories
3
Work History
August 2025
1 Commits • 1 Features
Aug 1, 2025In August 2025, the Solvro ML project focused on delivering foundational ML education assets to accelerate onboarding and hands-on skill development. The primary deliverables were two PyTorch-focused notebooks that cover both theory and practice in Neural Networks and Computer Vision, enabling rapid upskilling for developers and data scientists. No critical bugs were reported this month, while the new assets establish a solid foundation for future feature work and experimentation.
1 Commits • 1 Features
Aug 1, 2025In August 2025, the Solvro ML project focused on delivering foundational ML education assets to accelerate onboarding and hands-on skill development. The primary deliverables were two PyTorch-focused notebooks that cover both theory and practice in Neural Networks and Computer Vision, enabling rapid upskilling for developers and data scientists. No critical bugs were reported this month, while the new assets establish a solid foundation for future feature work and experimentation.
August 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Convolutional Neural Networks (CNNs)Data Loading and PreprocessingDeep LearningJupyter NotebooksModel Training and EvaluationNeural NetworksPyTorch
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