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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the concept of Principal Component Analysis (PCA) and its application in finding the directions of largest variance in a dataset. It explains how PCA can be used to reduce the dimensionality of data and visualize high-dimensional datasets. The lecture also discusses the process of decorrelating data using PCA, exploring the wine dataset, and the limitations of PCA in dimension reduction.
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