Lectures related to Data Compression: Entropy Definition

Data Compression: Shannon-Fano Algorithm

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

Entropy: Examples and Properties

Explores examples of guessing letters, origins of entropy, and properties in information theory.

Data Compression and Entropy Definition

Explores the concept of entropy as the average number of questions needed to guess a randomly chosen letter in a sequence, emphasizing its enduring relevance in information theory.

Data Compression and Shannon's Theorem Summary

Summarizes Shannon's theorem, emphasizing the importance of entropy in data compression.

Data Compression and Shannon's Theorem: Performance Analysis

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

Entropy and Algorithms

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