Basic Clustering for Complex Shapes

As a Data Scientist, there may be times when you need to find patterns in data without any pre-defined labels. This represents an unsupervised machine learning problem. While many techniques exist to address this issue, clustering is a common starting point. In this project, you will work on training and optimizing different clustering algorithms using various types of data. You will discover that there is no one-size-fits-all algorithm for clustering, and the best choice depends on the data shape and the evaluation method.