Lectures related to Data Compression and Shannon's Theorem Summary

Explores entropy, compression algorithms, and optimal coding methods for data compression.

Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.

Explores compression in stochastic processes through injective codes and prefix-free codes.

Explores the Shannon-Fano algorithm for efficient data compression and its applications in lossless and lossy compression techniques.

Explores conditional entropy and Huffman coding for efficient data compression techniques.

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.