Several chemical tests are performed on different white wines. The goal is to predict their quality based on those tests.

The quality is represented by a score between 0 and 10.

The input variables are (based on physicochemical tests):

1. fixed acidity
2. volatile acidity
3. citric acid
4. residual sugar
5. chlorides
6. free sulfur dioxide
7. total sulfur dioxide
8. density
9. pH
10. sulphates
11. alcohol

We separated the dataset by score, each quality of wine in its class/file. Thanks to our AI algorithms, we obtain great results, 99% accuracy. Which means 99% of the time, our model correctly predicted the quality of the wine.

And you could run all that on a microcontroller!