DBSCAN Clustering Algorithm

# Introduction

In this lab, we will use the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to cluster a synthetic dataset. DBSCAN is a clustering algorithm that identifies core samples in regions of high density and expands clusters from them. This algorithm is useful for data containing clusters of similar density.

## VM Tips

After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.