How information uncertainty is measured in bits
Shannon entropy, developed in 1948, measures information uncertainty in bits, forming the bedrock of data compression, error correction, and even understanding brain signals.
Shannon entropy, a concept from 1948, quantifies the average uncertainty or surprise in information, measured in bits. Imagine a fair coin flip: its 1 bit of entropy means two equally likely outcomes, each carrying one bit of information. A biased coin has less entropy, reflecting reduced uncertainty.
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