About this document
Backpropagation Example by mrcuteboychandru46 is a document available to read on EtoBox.
The document outlines a problem involving backpropagation in a simple neural network with one input neuron, a hidden layer of two neurons using ReLU activation, and one output neuron with linear activation. It details the feedforward pass, loss calculation using Mean Squared Error, and the backpropagation process to update the weights based on the gradients. After one update step, the new weights for the output layer are w3 = 0.3189 and w4 = 0.4378.
- Author
- mrcuteboychandru46
- Language
- EN