compbiozurich/UZH-BIO392
Apr 2026 – May 2026
2 Months active
Languages Used
MarkdownRPython
Technical Skills
R programmingdata analysisdata visualizationdocumentationstatistical analysisJupyter
peppinalou
PROFILE
Peppinalou
Contributed to the compbiozurich/UZH-BIO392 repository by developing three features over two months, focusing on reproducible data analysis and machine learning workflows. Delivered a comprehensive Jupyter notebook for CNV-based cancer type classification, covering data preparation, model training, and evaluation using Python, pandas, and scikit-learn. Enhanced course materials with detailed documentation and an R script demonstrating data exploration and visualization on the iris dataset, supporting onboarding and reproducibility. Emphasized clear documentation practices with Markdown and Git, providing reusable templates and structured workflows for students. The work established maintainable foundations for both statistical analysis and machine learning within the educational context.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
16,631
Activity Months2
Your Network
27 peopleShared Repositories
27
Work History
May 2026
1 Commits • 1 Features
May 1, 2026Monthly summary for 2026-05: Delivered an end-to-end CNV-based cancer type classification notebook for compbiozurich/UZH-BIO392, including data preparation, model training, and evaluation, targeting ovarian high-grade serous adenocarcinoma and glioblastoma. Introduced a reproducible ML workflow via a dedicated Jupyter notebook. No major bug fixes documented for this repo this month. Overall impact: provides a foundation for CNV-driven cancer subtype classification, enabling rapid experimentation and benchmarking. Technologies/skills demonstrated: Python, Jupyter notebooks, CNV data processing, ML modeling and evaluation, reproducible research practices.
1 Commits • 1 Features
May 1, 2026Monthly summary for 2026-05: Delivered an end-to-end CNV-based cancer type classification notebook for compbiozurich/UZH-BIO392, including data preparation, model training, and evaluation, targeting ovarian high-grade serous adenocarcinoma and glioblastoma. Introduced a reproducible ML workflow via a dedicated Jupyter notebook. No major bug fixes documented for this repo this month. Overall impact: provides a foundation for CNV-driven cancer subtype classification, enabling rapid experimentation and benchmarking. Technologies/skills demonstrated: Python, Jupyter notebooks, CNV data processing, ML modeling and evaluation, reproducible research practices.
May 2026
April 2026
3 Commits • 2 Features
Apr 1, 2026Month: 2026-04 — Delivered documentation enhancements and an end-to-end data exploration example for compbiozurich/UZH-BIO392, reinforcing course materials, submission workflows, and reproducibility. No major bugs fixed this period. Impact: clearer onboarding for course participants, more maintainable course results artifacts, and a ready-to-run data analysis template that demonstrates data loading, structure inspection, visualization, and basic statistics. Technologies/skills demonstrated: Markdown/README best practices, Git version control, and R scripting for data analysis and visualization.
April 2026
3 Commits • 2 Features
Apr 1, 2026Month: 2026-04 — Delivered documentation enhancements and an end-to-end data exploration example for compbiozurich/UZH-BIO392, reinforcing course materials, submission workflows, and reproducibility. No major bugs fixed this period. Impact: clearer onboarding for course participants, more maintainable course results artifacts, and a ready-to-run data analysis template that demonstrates data loading, structure inspection, visualization, and basic statistics. Technologies/skills demonstrated: Markdown/README best practices, Git version control, and R scripting for data analysis and visualization.
Activity
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Quality Metrics
Correctness100.0%
Maintainability95.0%
Architecture100.0%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonR
Technical Skills
JupyterR programmingdata analysisdata visualizationdocumentationmachine learningpandasscikit-learnstatistical analysis
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