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Neural Network Weights per input nodes
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Problem
Sorry, I'm really new to neural networks and this question is probably pretty obvious. If you have any resource that can help clarify these concepts to me it would be much appreciated.
The way I understand neural networks is that each input node, x i goes to each hidden layer. Is there a unique weight for each input that goes into each hidden node?
with xi being inputs, h being hidden layers, and O being the output. Would the weight from x1 to h1 be different from the weight from x1 to h2? If I'm not on the right track, please correct me!
The way I understand neural networks is that each input node, x i goes to each hidden layer. Is there a unique weight for each input that goes into each hidden node?
with xi being inputs, h being hidden layers, and O being the output. Would the weight from x1 to h1 be different from the weight from x1 to h2? If I'm not on the right track, please correct me!
Solution
Yes, each input value is weighted before being fed into the nodes in the next layer. Each input/output pair of "neurons" has its own weight and it is these weights that are adjusted by the neural network training process. The initial weights are typically random values before training begins.
Context
StackExchange Computer Science Q#29224, answer score: 2
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