# Introduction This lab is a step-by-step tutorial on how to perform Gaussian Process Regression (GPR) on Mauna Loa CO2 data using the scikit-learn package. The data consists of monthly average atmospheric CO2 concentrations collected at the Mauna Loa Observatory in Hawaii between 1958 and 2001. The objective is to model the CO2 concentration as a function of time and extrapolate it for years after 2001. ## 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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