DataBytes-Organisation/DiscountMate_new
Nov 2025 – Jan 2026
3 Months active
Languages Used
Pythontext
Technical Skills
Jupyter NotebookPythondata analysismachine learningAPI integrationCSV handling
kevke-edu
PROFILE
Kevke-edu
Kearney Kearney contributed to the DataBytes-Organisation/DiscountMate_new repository by developing features that enhanced data infrastructure, catalog scraping, and recommendation outputs. Over three months, Kearney built a multi-store catalogue scraper in Python that downloads product images, tracks metadata in CSV files, and supports backup and update workflows for data integrity. They improved Jupyter Notebook maintainability by cleaning outputs and surfacing KNN-based recommendations for product teams. Kearney also expanded datasets with 26,000 Coles URLs, introduced onboarding and governance tools, and established an experimental framework for deep learning research, demonstrating depth in data management, machine learning, and documentation throughout the development process.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
6
Lines of code
4,316,594
Activity Months3
Your Network
129 people
Work History
January 2026
4 Commits • 3 Features
Jan 1, 2026January 2026 monthly performance summary for DataBytes-Organisation/DiscountMate_new. Focused on expanding data infrastructure, governance tooling, and an experimental R&D framework to accelerate onboarding, improve data quality, and establish foundations for future development. Key work includes dataset expansion and policy documentation, a new onboarding discovery tool for governance reporting, and an experimental research structure with a CNN-based reverse image search PoC. All changes are traceable via commit history, including policy/readme clarifications and feature implementations.
4 Commits • 3 Features
Jan 1, 2026January 2026 monthly performance summary for DataBytes-Organisation/DiscountMate_new. Focused on expanding data infrastructure, governance tooling, and an experimental R&D framework to accelerate onboarding, improve data quality, and establish foundations for future development. Key work includes dataset expansion and policy documentation, a new onboarding discovery tool for governance reporting, and an experimental research structure with a CNN-based reverse image search PoC. All changes are traceable via commit history, including policy/readme clarifications and feature implementations.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for DataBytes-Organisation/DiscountMate_new focusing on feature delivery and business impact. Key feature delivered: Multi-store Catalogue Scraper with Image Downloads and Metadata CSV Tracking. Implemented a scalable module that scrapes product data across multiple Australian retailers, downloads product images, and records metadata in CSV format. The feature includes backup and update functionalities to ensure data integrity and refresh capability for catalogs.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for DataBytes-Organisation/DiscountMate_new focusing on feature delivery and business impact. Key feature delivered: Multi-store Catalogue Scraper with Image Downloads and Metadata CSV Tracking. Implemented a scalable module that scrapes product data across multiple Australian retailers, downloads product images, and records metadata in CSV format. The feature includes backup and update functionalities to ensure data integrity and refresh capability for catalogs.
November 2025
2 Commits • 2 Features
Nov 1, 2025Month: 2025-11 — DataBytes-Organisation/DiscountMate_new. Focused on delivering user-facing KNN results and improving code maintainability. No critical bugs reported this month; maintenance tasks centered on improving diff readability and reproducibility. Impact includes faster validation of KNN-driven recommendations by product teams and streamlined review workflows thanks to cleaner notebook outputs. Technologies/skills demonstrated: Python, KNN integration, Jupyter notebook hygiene, and strong commit discipline.
2 Commits • 2 Features
Nov 1, 2025Month: 2025-11 — DataBytes-Organisation/DiscountMate_new. Focused on delivering user-facing KNN results and improving code maintainability. No critical bugs reported this month; maintenance tasks centered on improving diff readability and reproducibility. Impact includes faster validation of KNN-driven recommendations by product teams and streamlined review workflows thanks to cleaner notebook outputs. Technologies/skills demonstrated: Python, KNN integration, Jupyter notebook hygiene, and strong commit discipline.
November 2025
Activity
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Quality Metrics
Correctness97.2%
Maintainability88.6%
Architecture94.2%
Performance85.8%
AI Usage34.2%
Skills & Technologies
Programming Languages
Pythontext
Technical Skills
API integrationCSV handlingJupyter NotebookPythonPython scriptingback end developmentdata analysisdata managementdata policy managementdata scrapingdeep learningdocumentationimage processingloggingmachine learning
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