Entropy and Information Theory

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Related lectures (29)

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Information Theory: Source Coding & Channel Coding

Covers the fundamentals of information theory, focusing on source coding and channel coding.

Data Compression and Entropy 2: Entropy as 'Question Game'

Explores entropy as a 'question game' to guess letters efficiently and its relation to data compression.

Biological Randomness and Data Analysis

Explores randomness in biology, covering thermal fluctuations, random walks, and data analysis techniques.

Chain Rule for Entropy

Explores the chain rule for entropy, decomposing uncertainty in random variables and illustrating its application with examples.

Data Compression and Entropy Interpretation

Explores the origins and interpretation of entropy, emphasizing its role in measuring disorder and information content in a system.

Quantifying Statistical Dependence: Covariance and Correlation

Explores covariance, correlation, and mutual information in quantifying statistical dependence between random variables.

Data Compression: Entropy Definition

Explores data compression through entropy definition, types, and practical examples, illustrating its role in efficient information storage and transmission.

Data Compression and Shannon's Theorem: Shannon's Theorem Demonstration

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

Information in Networked Systems: Functional Representation and Data Compression

Explores traditional information theory, data compression, data transmission, and functional representation lemmas in networked systems.