# Introduction This lab demonstrates how to use multi-output estimators to complete images. The goal is to predict the lower half of a face given its upper half. Different algorithms such as extremely randomized trees, k-nearest neighbors, linear regression, and ridge regression will be used to complete the lower half of the faces. The completed faces will be compared with the original faces to evaluate the performance of the 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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