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Data Compression: Entropy Definition
This lecture introduces the concept of data compression, focusing on the definition of entropy and its role in reducing memory space and transmission time. It covers the types of compression, such as lossless and lossy, and presents the Shannon-Fano algorithm. The lecture also explores the notion of entropy through interactive games and practical examples, illustrating how the redundancy in languages can be leveraged for efficient compression. Additionally, it discusses the relationship between entropy and the probability of letter occurrence, highlighting the fundamental principles behind information theory and its applications in various fields.