racousin/data_science_practice_2025
Sep 2025 – Oct 2025
2 Months active
Languages Used
JSONJupyter NotebookMarkdownPythonShell
Technical Skills
API IntegrationData AggregationData AnalysisData CleaningData CollectionData Engineering
cyruszhang36969-stack
PROFILE
Cyruszhang36969-stack
Cyrus Zhang developed a suite of end-to-end data science workflows and utilities in the racousin/data_science_practice_2025 repository, focusing on robust project structure and reusable tooling. He engineered pipelines for forecasting quantity sold across stores, predicting house prices, and preprocessing weather and electricity demand data, leveraging Python, Pandas, and Scikit-learn. His work included building Jupyter Notebooks for exploratory analysis, implementing object detection on satellite imagery using YOLO, and experimenting with large language models for mathematical reasoning. Emphasizing maintainability, he improved documentation and modularity, delivering well-structured, production-ready code that addressed real-world data challenges without reported critical bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
32Total
Bugs
0
Commits
32
Features
11
Lines of code
37,555
Activity Months2
Your Network
22 people
Work History
October 2025
17 Commits • 5 Features
Oct 1, 2025October 2025 summary for racousin/data_science_practice_2025: Key features delivered across data science workflows, foundational analytics pipelines, and documentation improvements. No major bugs fixed this month; maintenance focused on quality of docs and repo hygiene. Overall impact: improved data readiness for forecasting (weather/electricity), enhanced satellite imagery analysis groundwork (boat detection), strengthened financial time-series modeling, and expanded ML reasoning experimentation. Technologies demonstrated include Python, Jupyter, Ultralytics YOLO, data imputation, time-series analysis, and LLM prompting.
17 Commits • 5 Features
Oct 1, 2025October 2025 summary for racousin/data_science_practice_2025: Key features delivered across data science workflows, foundational analytics pipelines, and documentation improvements. No major bugs fixed this month; maintenance focused on quality of docs and repo hygiene. Overall impact: improved data readiness for forecasting (weather/electricity), enhanced satellite imagery analysis groundwork (boat detection), strengthened financial time-series modeling, and expanded ML reasoning experimentation. Technologies demonstrated include Python, Jupyter, Ultralytics YOLO, data imputation, time-series analysis, and LLM prompting.
October 2025
September 2025
15 Commits • 6 Features
Sep 1, 2025September 2025 across racousin/data_science_practice_2025 focused on delivering end-to-end data science capabilities, strengthening project structure, and introducing reusable tooling. No critical bugs were reported; the emphasis was on cleanup and maintainability to accelerate future development while delivering tangible business value through data pipelines and models.
September 2025
15 Commits • 6 Features
Sep 1, 2025September 2025 across racousin/data_science_practice_2025 focused on delivering end-to-end data science capabilities, strengthening project structure, and introducing reusable tooling. No critical bugs were reported; the emphasis was on cleanup and maintainability to accelerate future development while delivering tangible business value through data pipelines and models.
Activity
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Quality Metrics
Correctness88.8%
Maintainability90.2%
Architecture88.8%
Performance86.4%
AI Usage28.2%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPythonShell
Technical Skills
API IntegrationComputer VisionData AggregationData AnalysisData CleaningData CollectionData EngineeringData PreprocessingData ScienceData ScrapingData VisualizationDocumentationFile ManagementFinancial Time Series AnalysisHugging Face Transformers
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline