# Introduction The purpose of this lab is to show how to use the `LearningCurveDisplay` class from scikit-learn to plot learning curves. Learning curves show the effect of adding more samples during the training process. We will analyze the learning curve of a naive Bayes classifier and a SVM classifier with a RBF kernel using the digits dataset. Additionally, we will look at the scalability of these predictive models by looking at their computational cost and not only at their statistical accuracy. ## 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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