
During January 2025, Soyun developed a set of end-to-end Data Analysis and Modeling Tutorial Notebooks for the halley1116/2025_DA_study repository. The work focused on creating reproducible Jupyter Notebook templates that guide users through data loading, exploration, preprocessing, and basic modeling using Python, pandas, and XGBoost. Each notebook included clear steps for initial data inspection, descriptive statistics, and hands-on tutorials for exploratory data analysis and model training. By providing ready-to-run examples and structured workflows, Soyun enabled faster onboarding and self-service analytics for new data scientists, addressing the need for accessible, standardized data science resources within the team.

Concise monthly summary for 2025-01 highlighting the delivery and impact of the Data Analysis and Modeling Tutorial Notebooks in the halley1116/2025_DA_study repo. The work focused on delivering end-to-end, reproducible data science templates to accelerate onboarding and self-service analytics for the team.
Concise monthly summary for 2025-01 highlighting the delivery and impact of the Data Analysis and Modeling Tutorial Notebooks in the halley1116/2025_DA_study repo. The work focused on delivering end-to-end, reproducible data science templates to accelerate onboarding and self-service analytics for the team.
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