Lectures related to Claude Shannon's Story

Conditional Entropy and Data Compression Techniques

Discusses conditional entropy and its role in data compression techniques.

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 Entropy: Illustrating Entropy Properties

Explores entropy as a measure of disorder and how it can be increased.

Source Coding Theorems: Entropy and Source Models

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

Communication Amid Uncertainty

Explores challenges in human communication, context importance, compression problems, uncertain functionality, and proof verification.

Information Theory: Basics and Applications

Covers the basics of information theory and its applications in various fields.