https://github.com/danielc92/rain_prediction
Predicting whether it will rain the next day (in Australia) using machine learning models.
https://github.com/danielc92/rain_prediction
Last synced: about 2 months ago
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Predicting whether it will rain the next day (in Australia) using machine learning models.
- Host: GitHub
- URL: https://github.com/danielc92/rain_prediction
- Owner: danielc92
- Created: 2019-01-20T23:14:35.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-01-22T04:53:32.000Z (over 7 years ago)
- Last Synced: 2025-08-01T10:11:53.272Z (11 months ago)
- Language: Jupyter Notebook
- Size: 3.66 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Rain Prediction in Australia
Attempting to build a machine learning model(s) to predict whether it will rain the next day in Australia. The [dataset](https://www.kaggle.com/jsphyg/weather-dataset-rattle-package) used in this project has approx 140k rows and 24 features.
# Before you get started
- Good understanding of pandas library
- Intermediate understanding of sklearn library (random forest classifier, gridsearchCV, train test split)
- Basic usage of jupyter notebooks
# Setup
**How to obtain this repository:**
```sh
git clone https://github.com/danielc92/rain_prediction.git
```
**Modules/dependencies:**
- `pandas`
- `jupyter`
- `sklearn`
Install the following dependences:
```sh
cd /local/location/of/this/repo
pip install pandas jupyter sklearn
```
# Tests
- Feature engineering on source dataset
- Built model with/without `pandas.get_dummies` process
# Contributors
- Daniel Corcoran
# Sources
- [Dataset from `kaggle`](https://www.kaggle.com/jsphyg/weather-dataset-rattle-package)
- [Random Forest Classifier from `sklearn`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)