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-# Wine quality prediction
-Modelling a Kaggle dataset of [red wine properties and quality ratings](https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009). 
+This repository demonstrates how to integrate [GitHub Actions](https://docs.github.com/en/actions) to:
+
+- Automatically train a small Random Forest Regressor model on the [wine quality dataset](https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009).
+- Automatically log the training and other important model metrics to Weights and Biases (`wandb`). 
+- Cache Python dependencies so that old dependencies do not get installed each time a run is triggered. 
+- Generate a `metrics.csv` file after a run is successfully completed. 
+
+![](https://i.ibb.co/JqZWHDC/image.png)
+
+## Acknowledgements
+
+[This video](https://www.youtube.com/watch?v=9BgIDqAzfuA) by DVCorg helped me a lot to clear the initial concepts regarding GitHub Actions.