# Introduction In this lab, we will learn how to use cross-validation to visualize model predictions and errors using the `cross_val_predict` and `PredictionErrorDisplay` functions in scikit-learn. We will load the diabetes dataset, create an instance of a linear regression model, and use cross-validation to obtain an array of predictions. We will then use `PredictionErrorDisplay` to plot the actual versus predicted values, as well as the residuals versus predicted values. ## 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