dsi-clinic/CMAP
Nov 2024 – Dec 2024
2 Months active
Languages Used
Python
Technical Skills
Code FormattingConfiguration ManagementData HandlingData PreprocessingDeep LearningExperiment Tracking
ms475
PROFILE
Ms475
Over a two-month period, contributed to the dsi-clinic/CMAP repository by building features that improved data handling, visualization, and experiment tracking for geospatial machine learning workflows. Refactored dataset initialization to be configuration-driven, enhancing modularity and testability, and optimized DEM data loading using rasterio for efficient region extraction. Enhanced experiment reproducibility by strengthening WandB integration and output management. Developed tooling for DEM data statistics, including computation and documentation of sample means and standard deviations, and improved visualization reliability with standardized plotting. The work leveraged Python, PyTorch, and data processing skills, focusing on maintainable code quality, robust configuration management, and reproducible research practices.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
10Total
Bugs
0
Commits
10
Features
6
Lines of code
274
Activity Months2
Your Network
119 peopleShared Repositories
23
Alan ChermanMember
Alan ChermanMember
Alan ChermanMember
Anna PoonMember
Anna PoonMember
Anna PoonMember
Anna Elizabeth WoodardMember
Nathan HaasMember
cassiehaasMember
Work History
December 2024
5 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for CMAP (dsi-clinic) focusing on delivering enhanced visualization tooling and data statistics capabilities to improve model evaluation, reproducibility, and decision-making. The work aligns with performance goals by delivering tangible features and robust tooling with clear business value for data scientists and ML engineers.
5 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for CMAP (dsi-clinic) focusing on delivering enhanced visualization tooling and data statistics capabilities to improve model evaluation, reproducibility, and decision-making. The work aligns with performance goals by delivering tangible features and robust tooling with clear business value for data scientists and ML engineers.
December 2024
November 2024
5 Commits • 4 Features
Nov 1, 2024Concise monthly summary for 2024-11 highlighting key delivered features, major fixes, and impact for business value and technical excellence.
November 2024
5 Commits • 4 Features
Nov 1, 2024Concise monthly summary for 2024-11 highlighting key delivered features, major fixes, and impact for business value and technical excellence.
Activity
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Quality Metrics
Correctness84.0%
Maintainability88.0%
Architecture82.0%
Performance76.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Code FormattingCode RefactoringConfiguration ManagementData HandlingData PreprocessingData ProcessingData VisualizationDebuggingDeep LearningDocumentationExperiment TrackingGeospatial DataImage AnalysisImage ProcessingLinting
Repositories Contributed To
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