Lecture
Information Measures: Part 2
Description
This lecture covers information measures, including entropy, joint entropy, conditional entropy, mutual information, and Kullback-Leibler divergence. It explains the concepts using mathematical formulas and examples, emphasizing the importance of these measures in information theory and data processing applications.
Official source
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