# Introduction This lab demonstrates how to use Bayesian Ridge Regression to fit a polynomial curve to sinusoidal data. We will generate sinusoidal data with noise, fit it using a cubic polynomial and plot the true and predicted curves with log marginal likelihood (L) of these models, we can determine which one is better. ## 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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