vncsmyrnk / modelling-wine-classes

Study of wine classifications

Predicting wine classes

This project aims to develop a machine learning model for predicting wine types (classes) based on a set of analytical characteristics. The model will learn from historical data to identify patterns between the features (e.g., acidity, alcohol content) and the corresponding wine class.

We will explore and compare different machine learning algorithms suitable for classification tasks. Common choices include Support Vector Machines (SVM), Random Forests, or Logistic Regression.

This notebook will serve as a record of our exploration and development process as we build a machine learning model for wine classification.

The data is available at scikit-learn.org.

The final report is included on this notebook. It is also available at Kaggle