Backpropagation (machine learning)
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At the time the article was created Matt Adams had no recorded disclosures.View Matt Adams's current disclosures
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Backpropagation in supervised machine learning is the process used to calculate the gradient of the error function associated with each parameter weighting within a convoluted neural network (CNN). Essentially, the gradient estimates how the system parameters should change in order to optimize the network overall 1,2.
- 1. Nikhil Buduma, Nicholas Locascio. Fundamentals of Deep Learning. ISBN: 9781491925614
- 2. Stephen Marsland. Machine Learning. ISBN: 9781498759786