# Introduction In this lab, we will perform Principal Component Analysis (PCA) on the Iris dataset using Python scikit-learn. PCA is a technique used to reduce the dimensionality of a dataset while retaining as much variance as possible. In simpler terms, it helps to identify the most important features in a dataset and discard the less important ones. The Iris dataset is a famous dataset in the field of machine learning and contains information about the physical attributes of three different types of Iris flowers. ## 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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