This repository is a mirror for my Jupyter notebooks on Kaggle. It's automatically generated (including this README.md) and is updated once in a while. This notebooks collection will give you an insight on how I have been experimenting with exploratory data analysis (EDA), predicting target variables, and comparing model's performance. All explanation is included in the notebook.
I hope to learn more about data visualization and predictive analysis. I appreciate any comment and suggestion on my work. Thank you!
Note: This GitHub repository only mirrors the .ipynb files without the printed/saved cells output, due to Kaggle's API policy. To see the full visualization and output on Kaggle, please refer to the links on the index below!
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Last run time: 2020-11-05 03:52:49 UTC
🐍 Lang: Python | 📈 Dataset source |
GitHub link
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Last run time: 2020-11-01 02:24:57 UTC
🐍 Lang: Python | 📈 Dataset source |
GitHub link
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Last run time: 2020-10-31 14:21:05 UTC
🐍 Lang: Python | 📈 Dataset source |
GitHub link