# Introduction The `cross_decomposition` module in scikit-learn contains supervised estimators for dimensionality reduction and regression, specifically for Partial Least Squares (PLS) algorithms. These algorithms find the fundamental relationship between two matrices by projecting them into a lower-dimensional subspace such that the covariance between the transformed matrices is maximal. In this lab, we will explore the different cross decomposition algorithms provided by scikit-learn and learn how to use them for dimensionality reduction and regression tasks. ## 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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