Clustering Geolocation Data Intelligently in Python

Overview

In this 1.5-hour long project, you will learn how to clean and preprocess geolocation data for clustering. You will learn how to export this data into an interactive file that can be better understood for the data. You will learn how to cluster initially with a K-Means approach, before using a more complicated density-based algorithm, DBSCAN. We will discuss how to evaluate these models, and offer improvements to DBSCAN with the introduction of HDBSCAN. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.