# Introduction This lab compares two popular non-linear dimensionality techniques, Locally Linear Embedding (LLE) and T-distributed Stochastic Neighbor Embedding (t-SNE), on the classic Swiss Roll dataset. We will explore how they both deal with the addition of a hole in the data. ## 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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