https://github.com/luona-zhang/kaggle-data-science-competitions

This repository contains code developed for participating in Kaggle Data Science competitions.
https://github.com/luona-zhang/kaggle-data-science-competitions

fitting-algorithm machine-learning model-evaluation numpy pandas scikit-learn seaborn tensorflow

Last synced: 5 months ago
JSON representation

This repository contains code developed for participating in Kaggle Data Science competitions.

• Host: GitHub
• URL: https://github.com/luona-zhang/kaggle-data-science-competitions
• Owner: luona-zhang
• License: mit
• Created: 2025-06-19T10:32:41.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-06-20T12:21:29.000Z (6 months ago)
• Last Synced: 2025-06-20T13:26:15.841Z (6 months ago)
• Topics: fitting-algorithm, machine-learning, model-evaluation, numpy, pandas, scikit-learn, seaborn, tensorflow
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/
• Size: 408 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Kaggle-Data-Science-competitions

This repository contains Jupyter notebooks written using datasets found on Kaggle. This will be an ongoing journey as I expand my Data Science toolkit.

### Citations

- Anna Montoya and DataCanary. House Prices - Advanced Regression Techniques.

  https://kaggle.com/competitions/house-prices-advanced-regression-techniques, 2016. Kaggle

- Will Cukierski. Titanic - Machine Learning from Disaster. https://kaggle.com/competitions/titanic, 2012. Kaggle.