About this Repository

The goal of this repository is to use the Wine Customer Segmentation Dataset to succesfully extract key information that defines distinct clusters of wines through Principal Component Analysis and K-Means.

Published Kaggle Kernel:

• Wine K-Means Clustering

Model in this Repository:

• Wine K-Means Clustering

Wine Clusters

Wine K-Means Clustering

Problem

In this Kaggle Notebook we would try to answer the following question: given the diferent attributes of several wines, could we succesfully create clusters of them to extract key information that defines them?

Proposed Solution

We would use K-Means and Principal Component Analysis in order to cluster our different wines in three distinct groups.

Dependencies

• Visualization

  • Matplotlib
  • Seaborn

• Data Processing

  • Numpy
  • Pandas

• Regression

  • Sklearn

Wine Customer Segmentation

These data are the results of a chemical analysis of wines grown in the same region in Italy but derived from three different cultivars. The analysis determined the quantities of 13 constituents found in each of the three types of wines.