dsi-clinic/CMAP
Nov 2024 – Dec 2024
2 Months active
Languages Used
Jupyter NotebookMarkdownPythonShellBashYAML
Technical Skills
Configuration ManagementData AnalysisData ScienceData VisualizationDebuggingDeep Learning
Wxy-23
PROFILE
Wxy-23
Xiaoyue worked on the dsi-clinic/CMAP repository, focusing on building and refining experiment tracking, configuration management, and data analysis workflows over a two-month period. They introduced a debug mode and experimental tooling to accelerate model development, standardized configuration and data path handling, and improved integration with Weights & Biases for reproducible machine learning experiments. Using Python, SLURM, and GeoPandas, Xiaoyue enhanced hyperparameter sweep documentation and onboarding, fixed critical data visualization bugs in class distribution analysis, and reorganized project structure for maintainability. Their work demonstrated depth in MLOps, technical writing, and geospatial analysis, resulting in faster, more reliable experimentation cycles.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
19Total
Bugs
1
Commits
19
Features
7
Lines of code
1,614
Activity Months2
Your Network
110 people
Work History
December 2024
10 Commits • 2 Features
Dec 1, 2024Monthly performance summary for 2024-12 (dsi-clinic/CMAP). This period focused on enhancing experiment workflows, fixing critical data visualization issues, and improving repository maintainability to boost reproducibility and onboarding efficiency. Delivered measurable improvements to hyperparameter tuning with W&B and SLURM sweeps, corrected class distribution analysis, and restructured project layout.
10 Commits • 2 Features
Dec 1, 2024Monthly performance summary for 2024-12 (dsi-clinic/CMAP). This period focused on enhancing experiment workflows, fixing critical data visualization issues, and improving repository maintainability to boost reproducibility and onboarding efficiency. Delivered measurable improvements to hyperparameter tuning with W&B and SLURM sweeps, corrected class distribution analysis, and restructured project layout.
December 2024
November 2024
9 Commits • 5 Features
Nov 1, 2024Concise monthly summary for 2024-11 focused on CMAP development work. Delivered features, fixed critical issues, and advanced tooling to speed experimentation and improve reproducibility. Highlighted outcomes include debug tooling, streamlined experiment tracking, configuration normalization, comprehensive sprint documentation, and faster testing cycles with measurable business impact.
November 2024
9 Commits • 5 Features
Nov 1, 2024Concise monthly summary for 2024-11 focused on CMAP development work. Delivered features, fixed critical issues, and advanced tooling to speed experimentation and improve reproducibility. Highlighted outcomes include debug tooling, streamlined experiment tracking, configuration normalization, comprehensive sprint documentation, and faster testing cycles with measurable business impact.
Activity
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Quality Metrics
Correctness89.4%
Maintainability89.4%
Architecture85.2%
Performance82.2%
AI Usage23.2%
Skills & Technologies
Programming Languages
BashJupyter NotebookMarkdownPythonShellYAML
Technical Skills
Code OrganizationConfiguration ManagementData AnalysisData ScienceData VisualizationDebuggingDeep LearningDocumentationEnvironment ManagementExperiment TrackingGeoPandasGeospatial AnalysisHyperparameter TuningMachine LearningMachine Learning Operations (MLOps)
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