# Introduction In this lab, we will explore the k-means clustering algorithm and its assumptions. We will generate data with different distributions and visualize how k-means partitions this data into clusters. We will also discuss some of the limitations of the algorithm and possible solutions to overcome them. ## 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.
Click the virtual machine below to start practicing