Quant-of-Renmin-University/Quant_RUC
Sep 2025 – Dec 2025
4 Months active
Languages Used
CSSCSVHTMLPythonJupyter NotebookMarkdownUnknown
Technical Skills
Data AnalysisData ManagementDocument GenerationJupyter NotebooksPython ScriptingWeb Scraping
So-Ezzz
PROFILE
So-ezzz
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
13Total
Bugs
1
Commits
13
Features
7
Lines of code
7,417
Activity Months4
Your Network
109 people
Work History
December 2025
2 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Quant_RUC (Quant-of-Renmin-University/Quant_RUC) delivered a robust End-to-End Rental and Sales Price Prediction ML Pipeline. The project encompassed data preprocessing, feature engineering, and model training with multiple regression models, followed by evaluation and deployment preparation. Bugs encountered were stabilized through improvements to preprocessing and the evaluation workflow, reducing pipeline fragility. Overall impact includes data-driven pricing capabilities, faster iteration cycles, and a clear path to production deployment. Technologies and skills demonstrated include Python, scikit-learn, data munging, feature engineering, model selection and evaluation, and basic MLOps practices.
2 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Quant_RUC (Quant-of-Renmin-University/Quant_RUC) delivered a robust End-to-End Rental and Sales Price Prediction ML Pipeline. The project encompassed data preprocessing, feature engineering, and model training with multiple regression models, followed by evaluation and deployment preparation. Bugs encountered were stabilized through improvements to preprocessing and the evaluation workflow, reducing pipeline fragility. Overall impact includes data-driven pricing capabilities, faster iteration cycles, and a clear path to production deployment. Technologies and skills demonstrated include Python, scikit-learn, data munging, feature engineering, model selection and evaluation, and basic MLOps practices.
December 2025
November 2025
3 Commits • 2 Features
Nov 1, 20252025-11 monthly summary for Quant_RUC: Delivered an end-to-end Housing Price and Rent Prediction Modeling Pipeline via a new Jupyter notebook, integrating data cleaning, feature extraction, and model training with support for multiple models. Added Rent Prediction Model Validation Report detailing verification results, core dimensions, and optimization suggestions. No major bugs reported this month. Impact: faster experimentation, improved model quality, and governance-ready workflows that reduce deployment risk. Skills demonstrated: Python, Jupyter, data cleaning and feature engineering, model training/validation, and pipeline refactoring.
November 2025
3 Commits • 2 Features
Nov 1, 20252025-11 monthly summary for Quant_RUC: Delivered an end-to-end Housing Price and Rent Prediction Modeling Pipeline via a new Jupyter notebook, integrating data cleaning, feature extraction, and model training with support for multiple models. Added Rent Prediction Model Validation Report detailing verification results, core dimensions, and optimization suggestions. No major bugs reported this month. Impact: faster experimentation, improved model quality, and governance-ready workflows that reduce deployment risk. Skills demonstrated: Python, Jupyter, data cleaning and feature engineering, model training/validation, and pipeline refactoring.
October 2025
5 Commits • 2 Features
Oct 1, 2025October 2025 focused on delivering a data-driven real estate analytics workflow and boosting notebook visualization capabilities for Quant_RUC. Delivered a Python-based Fang.com scraping and analytics platform that collects second-hand housing and rental data, processes data, analyzes price and rent distributions across Beijing districts, detects outliers, computes price-to-rent ratio, and provides visualizations (box plots and bar charts). Enhanced notebook visuals by integrating seaborn, fixed plotting-related NameError issues, and updated dependencies to improve reliability. Included repository hygiene improvements with a placeholder commit to ensure traceability. These efforts establish a foundation for data-driven pricing insights and repeatable analytics in Beijing.
5 Commits • 2 Features
Oct 1, 2025October 2025 focused on delivering a data-driven real estate analytics workflow and boosting notebook visualization capabilities for Quant_RUC. Delivered a Python-based Fang.com scraping and analytics platform that collects second-hand housing and rental data, processes data, analyzes price and rent distributions across Beijing districts, detects outliers, computes price-to-rent ratio, and provides visualizations (box plots and bar charts). Enhanced notebook visuals by integrating seaborn, fixed plotting-related NameError issues, and updated dependencies to improve reliability. Included repository hygiene improvements with a placeholder commit to ensure traceability. These efforts establish a foundation for data-driven pricing insights and repeatable analytics in Beijing.
October 2025
September 2025
3 Commits • 2 Features
Sep 1, 2025September 2025 (2025-09) Monthly Summary for Quant_RUC: Key features delivered: - Finance Module Homework Assets for HW2: Added a new image asset and an accompanying README.md for the Finance module's HW2 assignment. Commit: ff1cb006a1ffc7e6628bfb4d55962a5ceb9d0be3. - University Application Document Generator (data-driven): Automated workflow to generate university application documents by scraping rankings and combining research areas, top journals, and required skills into a Word template. Includes a data-powered dataset (data.csv). Commits: 476f2744f6ce33dcfbda04f8fea31d190e15df4e; 9cf5b14f1bdc3dcacddcce8718eef2b7873b5e98. Major bugs fixed: - No major bugs fixed this month (none reported). Overall impact and accomplishments: - Delivered tangible, business-facing assets and automation: asset provisioning for coursework and a data-driven document generator that reduces manual drafting time and improves consistency. - Established a scalable workflow that can be reused for future university applications and coursework assets, with clear data inputs (data.csv) and a reproducible template (Word). Technologies/skills demonstrated: - Asset management (image assets, README metadata) and repository hygiene. - Data-driven automation, web ranking scraping, and Word template generation. - Data.csv-driven workflows and reproducible automation; strong emphasis on version control and commit traceability.
September 2025
3 Commits • 2 Features
Sep 1, 2025September 2025 (2025-09) Monthly Summary for Quant_RUC: Key features delivered: - Finance Module Homework Assets for HW2: Added a new image asset and an accompanying README.md for the Finance module's HW2 assignment. Commit: ff1cb006a1ffc7e6628bfb4d55962a5ceb9d0be3. - University Application Document Generator (data-driven): Automated workflow to generate university application documents by scraping rankings and combining research areas, top journals, and required skills into a Word template. Includes a data-powered dataset (data.csv). Commits: 476f2744f6ce33dcfbda04f8fea31d190e15df4e; 9cf5b14f1bdc3dcacddcce8718eef2b7873b5e98. Major bugs fixed: - No major bugs fixed this month (none reported). Overall impact and accomplishments: - Delivered tangible, business-facing assets and automation: asset provisioning for coursework and a data-driven document generator that reduces manual drafting time and improves consistency. - Established a scalable workflow that can be reused for future university applications and coursework assets, with clear data inputs (data.csv) and a reproducible template (Word). Technologies/skills demonstrated: - Asset management (image assets, README metadata) and repository hygiene. - Data-driven automation, web ranking scraping, and Word template generation. - Data.csv-driven workflows and reproducible automation; strong emphasis on version control and commit traceability.
Activity
Loading activity data...
Quality Metrics
Correctness75.4%
Maintainability75.4%
Architecture73.8%
Performance72.4%
AI Usage35.4%
Skills & Technologies
Programming Languages
CSSCSVHTMLJupyter NotebookMarkdownPythonUnknown
Technical Skills
Beautiful Soup (lxml)Data AnalysisData CleaningData ManagementData VisualizationDocument GenerationJupyter NotebookJupyter NotebooksLightGBMMatplotlibOutlier DetectionPandasPythonPython ScriptingRequests
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline