To group the wine dataset using clustering technique, specifically k-means clustering.
Clustering: Our goal in this exercise is to group the wines into clusters to find natural groups of objects wherein objects within groups are similar and objects within different groups are dissimilar. That is grouping the wines into clusters which have similar physical and chemical properties. k-Means algorithm has been used to build a clustering model with 2 clusters (k= 2). All the physical and chemical properties have been used to group the wines (except the quality rating ).