# Introduction In this lab, we will learn about different initialization methods for Gaussian Mixture Models (GMM). We will use scikit-learn library to generate sample data and visualize the clustering results. There are four different methods for the initialization parameter _init_param_: `kmeans` (default), `random`, `random_from_data`, and `k-means++`. ## 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