# Introduction Multi-dimensional scaling (MDS) is a technique used to visualize high-dimensional data in a lower dimensional space (usually 2D or 3D) while preserving the pairwise distances between the data points as much as possible. It is often used in exploratory data analysis and visualization. In this tutorial, we will walk through the steps of performing MDS on a generated noisy dataset using the scikit-learn library in Python. ## 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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