The purpose of this task is to cluster drug users using K-means clustering and Hierarchical Agglomerative clustering models and to visualize clusters for predicted and actual cluster labels. The dataset is part of "Drug consumption". More information here: https://archive.ics.uci.edu/ml/datasets/Drug+consumption+%28quantified%29#. The class attribute has been transformed into a binary classification where '0' indicates NOUSER and '1' indicates USER. In this task, elbow method has been used to determine the optimal number of clusters for k-means clustering. Since the dataset has multiple features(dimensions),data has been visualized with the help of one of the Dimensionality Reduction techniques, namely Principal Component Analysis (PCA).