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by scarlac
2171 days ago
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Neurons have weight and bias. Weight is multiplied, bias is added. Really that simple. Here are examples of equivalent notations that may make it more familiar: y = 2⋅x + b or
y = a⋅x + b
- x would be the input to the neuron, often named 'x'.- a/2 would be the weight, often named 'w'. - b would be the bias, often named 'b'. - y is the output. In neural network documentation this is often written as (often case sensitive, which may be confusing):
output = w⋅x + b (output = weight * input + bias). I hope that explains it. |
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