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Backpropagation Learning in Neural Networks by asmaa.alkholy is a document available to read on EtoBox.
Chapter 6 discusses backpropagation learning in multiple-layer networks, focusing on how input vectors and target vectors are used for training. It explains the architecture of neuron models, the use of non-linear units, and the application of the backpropagation algorithm to minimize error through gradient descent. The chapter also provides examples illustrating the weight adjustment process in a neural network.
- Author
- asmaa.alkholy
- Language
- EN