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Vocabulary

Understand the term. Connect the concept.

A practical dictionary of 512 AI, machine learning, mathematics, and programming terms from HerbDev’s AI Vocabulary app. Start with a definition, explore an example, then follow the concepts behind it.

Linked concepts open in a new tab. Audio reads the definition and example.

Entropy

Statistics & Probability · Level 2 of 5

Entropy

A measure of uncertainty in a probability distribution.

For discrete distributions it is the expected negative log probability of an outcome.

Example

A fair coin has more entropy than a coin that almost always lands heads.

Listen to the definition and example

Audio transcript

Entropy. A measure of uncertainty in a probability distribution. For discrete distributions it is the expected negative log probability of an outcome. For example: A fair coin has more entropy than a coin that almost always lands heads.

Explore this concept

A useful analogy

How much surprise remains before seeing the outcome.

Why it matters

This helps you interpret numerical evidence without overstating what it establishes.

Technical detail

H(p) = −Σ p_i log p_i with 0 log 0 interpreted as zero. Log base two yields bits.

Common misconception

Entropy concerns a distribution, not whether one specific output is correct.

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Related concepts

Quick recall question

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Put the terminology into context: How AI works · Machine-native representations · All learning paths

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