DiscoverData Science DecodedData Science #4 - "A Mathematical Theory of Communication" (1948), Shannon, C. E. Part - 2
Data Science #4 - "A Mathematical Theory of Communication" (1948), Shannon, C. E. Part - 2

Data Science #4 - "A Mathematical Theory of Communication" (1948), Shannon, C. E. Part - 2

Update: 2024-07-21
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Shannon, Claude Elwood. "A mathematical theory of communication." The Bell system technical journal 27.3 (1948): 379-423.

Part 2/3.

The paper fundamentally reshapes how we understand communication.

The paper introduces a formal framework for analyzing communication systems, addressing the transmission of information with and without noise. Key concepts include the definition of information entropy, the logarithmic measure of information, and the capacity of communication channels.

Shannon demonstrates that information can be efficiently encoded and decoded to maximize the transmission rate while minimizing errors introduced by noise. This work is pivotal today as it underpins digital communication technologies, from data compression to error correction in modern telecommunication systems.

Full breakdown of the paper with math and python code is at our website:
https://datasciencedecodedpodcast.com...

This is the second part out of 3, as the paper is quite long!

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Data Science #4 - "A Mathematical Theory of Communication" (1948), Shannon, C. E. Part - 2

Data Science #4 - "A Mathematical Theory of Communication" (1948), Shannon, C. E. Part - 2

Mike E