
Mabel Ng developed a real-time customer segmentation engine for the Yihe-Harry/DSA3101-Group-Project, focusing on scalable analytics and repository maintainability. She implemented an end-to-end pipeline using Python and Jupyter Notebook, integrating KMeans clustering with PCA visualization to enable dynamic updates and demonstrate business impact. Her work included data loading, preprocessing, and asset integration, as well as refactoring the repository structure to support onboarding and reproducibility. Mabel also improved documentation and standardized file organization, ensuring the project was customer-ready for segmentation pilots. The depth of her contributions established a robust foundation for future analytics and collaborative development within the team.

April 2025 monthly summary for Yihe-Harry/DSA3101-Group-Project. Focused on establishing a scalable, customer-ready foundation for real-time segmentation by refactoring repo structure and delivering essential documentation. The work improves onboarding, reproducibility, and readiness for customer pilots while setting the stage for subsequent feature work.
April 2025 monthly summary for Yihe-Harry/DSA3101-Group-Project. Focused on establishing a scalable, customer-ready foundation for real-time segmentation by refactoring repo structure and delivering essential documentation. The work improves onboarding, reproducibility, and readiness for customer pilots while setting the stage for subsequent feature work.
March 2025 monthly summary for the Yihe-Harry/DSA3101-Group-Project highlighting delivered capabilities, maintenance efforts, and business impact. Focused on real-time analytics, data scaffolding, and repository hygiene to empower faster decisioning and scalable analytics.
March 2025 monthly summary for the Yihe-Harry/DSA3101-Group-Project highlighting delivered capabilities, maintenance efforts, and business impact. Focused on real-time analytics, data scaffolding, and repository hygiene to empower faster decisioning and scalable analytics.
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