Lectures related to Data Compression and Shannon's Theorem: Shannon-Fano Coding

Explores entropy's role in coding strategies and search algorithms, showcasing its impact on information compression and data efficiency.

Introduces Shannon's Theorem on binary codes, entropy, and data compression limits.

Covers source coding theorems, entropy, and various source models in information theory.

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

Explores lossless compression using Shannon-Fano and Huffman algorithms, showcasing Huffman's superior efficiency and speed over Shannon-Fano.