# Introduction In this lab, we will compare two clustering algorithms: K-Means and MiniBatchKMeans. K-Means is a popular clustering algorithm that is widely used in machine learning. MiniBatchKMeans is a variant of K-Means that is faster but gives slightly different results. We will cluster a set of data using both algorithms and plot the results. We will also plot the points that are labeled differently between the two algorithms. ## 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.
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