📚 node [[mini batch|mini batch]]
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⥅ related node [[mini batch]]
⥅ related node [[mini batch_stochastic_gradient_descent_(sgd)]]
⥅ node [[mini-batch]] pulled by Agora
📓 garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Mini-Batch.md by @KGBicheno

mini-batch

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A small, randomly selected subset of the entire batch of examples run together in a single iteration of training or inference. The batch size of a mini-batch is usually between 10 and 1,000. It is much more efficient to calculate the loss on a mini-batch than on the full training data.
⥅ node [[mini-batch_stochastic_gradient_descent_(sgd)]] pulled by Agora
📓 garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Mini-Batch_Stochastic_Gradient_Descent_(Sgd).md by @KGBicheno

mini-batch stochastic gradient descent (SGD)

Go back to the [[AI Glossary]]

A gradient descent algorithm that uses mini-batches. In other words, mini-batch SGD estimates the gradient based on a small subset of the training data. Vanilla SGD uses a mini-batch of size 1.
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