Compression: Strong Connection and Prefix-Free Codes

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Compression

Covers the concept of compression and constructing prefix-free codes based on given information.

Compression: Prediction

Covers the concepts of compression and prediction using prefix-free codes and distributions.

Elements of Statistics: Probability and Random Variables

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Data Compression and Shannon's Theorem: Entropy Calculation Example

Demonstrates the calculation of entropy for a specific example, resulting in an entropy value of 2.69.

Entropy and Data Compression: Huffman Coding Techniques

Discusses entropy, data compression, and Huffman coding techniques, emphasizing their applications in optimizing codeword lengths and understanding conditional entropy.

Advanced Probabilities: Random Variables & Expected Values

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Conditional Entropy and Data Compression Techniques

Discusses conditional entropy and its role in data compression techniques.

Continuous Random Variables: Basic Ideas

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Compression: Kraft Inequality

Explains compression and Kraft inequality in codes and sequences.

Probability and Statistics

Covers probability distributions, moments, and continuous random variables.