Backpropagation — ML Glossary documentation


Resource | v1 | created by janarez |
Type Cheat sheet
Created 2017
Identifier unavailable

Description

The goals of backpropagation are straightforward: adjust each weight in the network in proportion to how much it contributes to overall error. If we iteratively reduce each weight’s error, eventually we’ll have a series of weights that produce good predictions.

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about Backpropagation

In machine learning, backpropagation (backprop, BP) is a widely used algorithm for training feedforwa...


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