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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 explains Shannon's theorem, stating that the compression of a source cannot go below its entropy. It also discusses the performance of Shannon Fano codes, showing they are close to the theoretical optimum. The relationship between entropy and the average number of questions in a Shannon Fano code is explored, providing insights into the exact definition of entropy.