Covers information measures like entropy, Kullback-Leibler divergence, and data processing inequality, along with probability kernels and mutual information.
Explores data compression through entropy definition, types, and practical examples, illustrating its role in efficient information storage and transmission.
Discusses entropy, data compression, and Huffman coding techniques, emphasizing their applications in optimizing codeword lengths and understanding conditional entropy.
