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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.

SGD

Optimization · Level 2 of 5

SGD (SGD)

Gradient descent using sampled examples or mini-batches to estimate gradients.

The stochastic estimate introduces noise compared with a full-data gradient.

Example

A model updates from a randomly selected batch rather than the entire dataset.

Listen to the definition and example

Audio transcript

SGD. Gradient descent using sampled examples or mini-batches to estimate gradients. The stochastic estimate introduces noise compared with a full-data gradient. For example: A model updates from a randomly selected batch rather than the entire dataset.

Explore this concept

A useful analogy

Estimating the downhill direction from a small sample of the landscape.

Why it matters

This helps you understand what parameter updates are trying to improve and when they can fail.

Technical detail

A mini-batch gradient averages ∇ℓ_i(θ) over sampled examples. Under suitable sampling it estimates the full-data gradient.

Common misconception

The stochastic gradient is an estimate, not necessarily the exact full-dataset direction.

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Related concepts

Quick recall question

Try answering before looking back at the definition.

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

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