Lectures related to Data Compression and Shannon's Theorem: Recap

Introduces data compression, exploring how redundancy in data can be reduced to achieve smaller file sizes without losing information.

Explores the cutting-edge JPEG XS and JPEG XL image compression standards, emphasizing their efficiency and versatility in various applications.

Explores Shannon's theorem on data compression and the performance of Shannon Fano codes.

Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.

Covers the demonstration of Shannon's theorem, focusing on data compression.

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