HWTeng-Teaching/202509-ML-FinTech
Sep 2025 – Nov 2025
3 Months active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Data AnalysisData VisualizationDocumentationExploratory Data AnalysisExploratory Data Analysis (EDA)Matplotlib
AyeMya13
PROFILE
Ayemya13
Aye Mya Thandar contributed to the HWTeng-Teaching/202509-ML-FinTech repository by developing a suite of Jupyter notebooks and project scaffolding to support data science coursework. Over three months, she delivered ten features including exploratory data analysis, clustering, regression modeling, and PCA workflows, using Python, Pandas, and Scikit-learn. Her work emphasized reproducibility and maintainability through clear documentation, structured directory layouts, and transparent commit histories. By implementing hands-on materials for datasets such as Boston housing and AutoData, she enabled rapid onboarding and curriculum delivery. The depth of her contributions provided a robust foundation for collaborative, modular, and scalable machine learning education.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
27Total
Bugs
0
Commits
27
Features
10
Lines of code
25,172
Activity Months3
Your Network
19 people
Work History
November 2025
11 Commits • 3 Features
Nov 1, 2025November 2025: Delivered three notebook-based features in HWTeng-Teaching/202509-ML-FinTech, focusing on data analysis, predictive ML workflows, and math-focused tooling. Features were implemented with clear commit history to support reproducibility and onboarding. No major bugs were reported in this period.
11 Commits • 3 Features
Nov 1, 2025November 2025: Delivered three notebook-based features in HWTeng-Teaching/202509-ML-FinTech, focusing on data analysis, predictive ML workflows, and math-focused tooling. Features were implemented with clear commit history to support reproducibility and onboarding. No major bugs were reported in this period.
November 2025
October 2025
9 Commits • 5 Features
Oct 1, 2025October 2025 — HWTeng-Teaching/202509-ML-FinTech: Established a scalable ML coursework foundation with project scaffolding and a suite of end-to-end notebooks spanning clustering and regression workflows. Implemented a robust directory structure (including a placeholder HW2 directory under xxxx_NAME/2020_AyeMya) to support modular content expansion and reproducible teaching materials. Delivered hands-on materials for clustering (hierarchical with complete and single linkage; K-means), regression analyses (AutoData with multiple linear regression, including data loading, descriptive stats, correlations, interactions, and diagnostic plots), Boston housing regression (simple, multiple, and polynomial models with visualizations), and PCA-enabled clustering analysis. These materials enable rapid curriculum delivery, reproducible experiments, and improved onboarding for learners and instructors.
October 2025
9 Commits • 5 Features
Oct 1, 2025October 2025 — HWTeng-Teaching/202509-ML-FinTech: Established a scalable ML coursework foundation with project scaffolding and a suite of end-to-end notebooks spanning clustering and regression workflows. Implemented a robust directory structure (including a placeholder HW2 directory under xxxx_NAME/2020_AyeMya) to support modular content expansion and reproducible teaching materials. Delivered hands-on materials for clustering (hierarchical with complete and single linkage; K-means), regression analyses (AutoData with multiple linear regression, including data loading, descriptive stats, correlations, interactions, and diagnostic plots), Boston housing regression (simple, multiple, and polynomial models with visualizations), and PCA-enabled clustering analysis. These materials enable rapid curriculum delivery, reproducible experiments, and improved onboarding for learners and instructors.
September 2025
7 Commits • 2 Features
Sep 1, 2025September 2025: Delivered foundational documentation and data science workflow for HWTeng-Teaching/202509-ML-FinTech. Implemented a project documentation skeleton with author metadata and introduced a Boston Housing Data EDA notebook to enable reproducible analyses, positioning the project for faster onboarding and iterative feature work. No major bugs observed; work emphasizes maintainability and business value.
7 Commits • 2 Features
Sep 1, 2025September 2025: Delivered foundational documentation and data science workflow for HWTeng-Teaching/202509-ML-FinTech. Implemented a project documentation skeleton with author metadata and introduced a Boston Housing Data EDA notebook to enable reproducible analyses, positioning the project for faster onboarding and iterative feature work. No major bugs observed; work emphasizes maintainability and business value.
September 2025
Activity
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Quality Metrics
Correctness89.0%
Maintainability83.8%
Architecture81.4%
Performance79.2%
AI Usage23.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
ClusteringData AnalysisData CleaningData ScienceData VisualizationDocumentationExploratory Data AnalysisExploratory Data Analysis (EDA)Hierarchical ClusteringJupyter NotebookK-Means ClusteringLinear RegressionMachine LearningMatplotlibNumPy
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