ABrain-One/nn-dataset
Sep 2025 – Oct 2025
2 Months active
Languages Used
Python
Technical Skills
Convolutional Neural Networks (CNNs)Deep LearningNeural NetworksPyTorchCNNComputer Vision
Raghuvir Duvvuri
PROFILE
Raghuvir Duvvuri
Developed and integrated advanced neural network model suites within the ABrain-One/nn-dataset repository, focusing on expanding evaluation coverage and enabling scalable experimentation for machine learning research. Leveraging Python and PyTorch, the work introduced 178 new neural network architectures and a configurable framework for exploring convolutional neural network (CNN) designs, layer configurations, and hyperparameters. This approach facilitated the automated generation and benchmarking of over 400 models for image classification tasks, supporting rapid identification of high-potential architectures. The engineering effort emphasized maintainability and reproducibility, aligning data structures and code to support future model zoo expansion and streamlined research workflows without major bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
49,738
Activity Months2
Your Network
61 peopleSame Organization
@stud-mail.uni-wuerzburg.de3
Shared Repositories
58
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ahsan89-ossMember
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ABrain-OneMember
Work History
October 2025
3 Commits • 1 Features
Oct 1, 2025October 2025: Delivered a scalable Neural Network Architecture Exploration feature for image classification in ABrain-One/nn-dataset. Implemented a configurable framework to define multiple CNN architectures, layer configurations, and hyperparameters, enabling rapid experimentation and benchmarking. Generated and evaluated 409 models across varying prompt configurations and supporting models to identify candidate architectures for production.
3 Commits • 1 Features
Oct 1, 2025October 2025: Delivered a scalable Neural Network Architecture Exploration feature for image classification in ABrain-One/nn-dataset. Implemented a configurable framework to define multiple CNN architectures, layer configurations, and hyperparameters, enabling rapid experimentation and benchmarking. Generated and evaluated 409 models across varying prompt configurations and supporting models to identify candidate architectures for production.
October 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered an expanded Neural Network Model Suite in the ABrain-One/nn-dataset repository, introducing 178 new neural network architectures and associated Python files into the dataset pipeline to broaden evaluation coverage and enhance research-ready performance. The work was implemented under commit 616d9f475f174d7c76a4c77832962784876b7547 and establishes a scalable foundation for future model zoo expansion and reproducible benchmarking. No major bugs were fixed this month; the primary focus was feature expansion and pipeline integration to accelerate experimentation and business value through richer evaluation capabilities.
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered an expanded Neural Network Model Suite in the ABrain-One/nn-dataset repository, introducing 178 new neural network architectures and associated Python files into the dataset pipeline to broaden evaluation coverage and enhance research-ready performance. The work was implemented under commit 616d9f475f174d7c76a4c77832962784876b7547 and establishes a scalable foundation for future model zoo expansion and reproducible benchmarking. No major bugs were fixed this month; the primary focus was feature expansion and pipeline integration to accelerate experimentation and business value through richer evaluation capabilities.
Activity
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Quality Metrics
Correctness75.0%
Maintainability75.0%
Architecture75.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
CNNComputer VisionConvolutional Neural Networks (CNNs)Deep LearningNeural NetworksPyTorch
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