Difference between revisions of "Backpropagation"
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* [[Gradient Descent Optimization & Challenges]] | * [[Gradient Descent Optimization & Challenges]] | ||
* [[Objective vs. Cost vs. Loss vs. Error Function]] | * [[Objective vs. Cost vs. Loss vs. Error Function]] | ||
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| + | [http://developers.google.com/machine-learning/glossary/ The primary algorithm for performing gradient descent on neural networks. First, the output values of each node are calculated (and cached) in a forward pass. Then, the partial derivative of the error with respect to each parameter is calculated in a backward pass through the graph. Machine Learning Glossary | Google] | ||
<youtube>q555kfIFUCM</youtube> | <youtube>q555kfIFUCM</youtube> | ||
Revision as of 23:07, 9 December 2018
