# Introduction This lab demonstrates the use of FastICA and PCA algorithm, two popular independent component analysis techniques. Independent Component Analysis (ICA) is a method of separating multivariate signals into additive subcomponents that are maximally independent. This technique finds directions in the feature space corresponding to projections with high non-Gaussianity. ## 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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