securefederatedai/openfl
Nov 2024 – Jan 2025
2 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
Data ScienceFederated LearningMachine LearningOpenFLPython
Kush Agrawal
PROFILE
Kush Agrawal
Worked on the securefederatedai/openfl repository to enhance onboarding and workflow clarity for federated learning with linear regression. Developed an end-to-end OpenFL tutorial in Jupyter Notebook, demonstrating model definition, synthetic data generation, federated training, and evaluation, which provided a reproducible resource for new users. Subsequently streamlined the NumPy linear regression workflow sample by removing unnecessary stdout redirection and simplifying collaborator iteration logic, improving execution reliability and reducing onboarding friction. Leveraged Python, NumPy, and the OpenFL framework throughout, focusing on reproducibility, code clarity, and maintainability. No bugs were fixed, reflecting stability in the delivered features and workflow improvements.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
581
Activity Months2
Your Network
2139 peopleSame Organization
@intel.com2109
Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for securefederatedai/openfl. Focused on streamlining the NumPy linear regression workflow sample within the OpenFL framework to improve reliability, clarity, and onboarding for contributors. Key changes reduced noise from stdout, simplified collaborator iteration logic, and clarified execution flow, with planned exclusion of 'private' collaborators in the next step.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for securefederatedai/openfl. Focused on streamlining the NumPy linear regression workflow sample within the OpenFL framework to improve reliability, clarity, and onboarding for contributors. Key changes reduced noise from stdout, simplified collaborator iteration logic, and clarified execution flow, with planned exclusion of 'private' collaborators in the next step.
January 2025
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for securefederatedai/openfl: Delivered a new OpenFL Federated Learning Tutorial for Linear Regression, enabling end-to-end demonstration of model definition, synthetic data generation, federated training workflow, and evaluation. This work strengthens onboarding, showcases practical federated learning patterns, and adds tangible developer value.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for securefederatedai/openfl: Delivered a new OpenFL Federated Learning Tutorial for Linear Regression, enabling end-to-end demonstration of model definition, synthetic data generation, federated training workflow, and evaluation. This work strengthens onboarding, showcases practical federated learning patterns, and adds tangible developer value.
Activity
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Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture85.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data ScienceFederated LearningMachine LearningOpenFLPython
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