d2cml-ai/Data-Science-Python
Apr 2025 – Jun 2025
2 Months active
Languages Used
CSVHTMLJSONJupyter NotebookPythonTextipynbSQL
Technical Skills
API IntegrationCSV HandlingData AnalysisData CleaningData EngineeringData Extraction
Sebasgp29
PROFILE
Sebasgp29
Over a two-month period, contributed to the d2cml-ai/Data-Science-Python repository by developing end-to-end data pipelines and analytical tooling focused on data acquisition, processing, and reproducibility. Built a Selenium-based job postings scraper for Bumeran.com.pe with CSV export, and engineered a Codeforces contest data fetcher that consolidates results for analysis. Established project scaffolding and improved repository hygiene to support maintainability. Delivered a geospatial analysis pipeline for Peru’s protected areas using Python, GeoPandas, and satellite data, and implemented machine learning benchmarking comparing CPU and GPU performance on vision and NLP tasks. Emphasized traceable commits, standardized formats, and scalable, reproducible workflows throughout.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
18Total
Bugs
0
Commits
18
Features
5
Lines of code
13,341
Activity Months2
Your Network
32 peopleWork History
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for d2cml-ai/Data-Science-Python: Delivered two end-to-end data science features and a benchmarking suite, with traceable commits. Focus on business value: improved environmental data capabilities and hardware-aware ML benchmarking.
2 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for d2cml-ai/Data-Science-Python: Delivered two end-to-end data science features and a benchmarking suite, with traceable commits. Focus on business value: improved environmental data capabilities and hardware-aware ML benchmarking.
June 2025
April 2025
16 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for d2cml-ai/Data-Science-Python: Delivered end-to-end data tooling and repository hygiene to accelerate analytics, reproducibility, and onboarding. Implemented data collection pipelines for market and coding contest data, plus a solid scaffolding foundation for future work. Business value was realized through reliable data exports, standardized formats, and a maintainable codebase ready for scaling.
April 2025
16 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for d2cml-ai/Data-Science-Python: Delivered end-to-end data tooling and repository hygiene to accelerate analytics, reproducibility, and onboarding. Implemented data collection pipelines for market and coding contest data, plus a solid scaffolding foundation for future work. Business value was realized through reliable data exports, standardized formats, and a maintainable codebase ready for scaling.
Activity
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Quality Metrics
Correctness90.6%
Maintainability90.0%
Architecture88.8%
Performance87.8%
AI Usage27.8%
Skills & Technologies
Programming Languages
CSVHTMLJSONJupyter NotebookPythonSQLTextipynb
Technical Skills
API IntegrationCSV HandlingData AcquisitionData AnalysisData CleaningData EngineeringData ExtractionData OrganizationData ProcessingData ScienceData ScrapingData VisualizationDeep LearningDependency ManagementFile Management
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline