zahariesergiu/ubb-sociology-ml
Feb 2026 – Feb 2026
1 Month active
Languages Used
Python
Technical Skills
data analysisdata preprocessingdata visualizationexploratory data analysisfeature engineeringmachine learning
ioanazah09
PROFILE
Ioanazah09
Ioana Zaharie developed a Census Data Analysis Notebook for the zahariesergiu/ubb-sociology-ml repository, focusing on preparing census data for machine learning modeling. She established workflows for data preprocessing, feature engineering, and exploratory data analysis using Python and Jupyter notebooks, ensuring the dataset was ready for subsequent modeling phases. When issues arose, she implemented a rollback of recent changes to the ML notebook and data models, stabilizing the codebase and maintaining project integrity. Her work emphasized reproducibility and commit-level traceability, demonstrating skills in data wrangling, visualization, and collaborative version control. The project laid a solid foundation for future modeling efforts.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
137,844
Activity Months1
Your Network
2 peopleShared Repositories
2
Work History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 achievements for zahariesergiu/ubb-sociology-ml: Delivered a Census Data Analysis Notebook and Modeling Preparation to establish preprocessing, feature engineering, and exploratory data analysis workflows, enabling modeling readiness. Implemented a rollback to revert ML notebook and data models changes after issues, stabilizing the codebase. Overall, this work advances data readiness, reduces risk, and sets a solid foundation for the modeling phase. Technologies demonstrated include Jupyter notebooks, data wrangling, feature engineering, EDA, and Git-based collaboration with Ioana Zaharie.
2 Commits • 1 Features
Feb 1, 2026February 2026 achievements for zahariesergiu/ubb-sociology-ml: Delivered a Census Data Analysis Notebook and Modeling Preparation to establish preprocessing, feature engineering, and exploratory data analysis workflows, enabling modeling readiness. Implemented a rollback to revert ML notebook and data models changes after issues, stabilizing the codebase. Overall, this work advances data readiness, reduces risk, and sets a solid foundation for the modeling phase. Technologies demonstrated include Jupyter notebooks, data wrangling, feature engineering, EDA, and Git-based collaboration with Ioana Zaharie.
February 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
data analysisdata preprocessingdata visualizationexploratory data analysisfeature engineeringmachine learning
Repositories Contributed To
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