A Study of KMeans Clustering

In this project, we will study and implement KMeans algorithm. The k-means algorithm is normally the most known and used clustering method. It is an unsupervised clustering method as it doesn’t require any labels for the data to be clustered in homogeneous groups. We will study all the procedures that are required to develop a kmeans clustering model. Elbow method is used to determine the optimal number of clusters. Here, we will use customer data in order to segment or cluster them into multiple homogeneous groups using kmeans algorithm.

Keywords: Unsupervised Learning, KMeans, Clustering, Elbow method.