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Neural network forward pass
Weights, bias, activation, made visible. Change the inputs and step through it.
Neural network forward pass: what it shows
A neural network is layers of simple units. Each unit multiplies its inputs by weights, adds a bias, and squashes the sum with an activation function. Change the two inputs and the activation (ReLU or sigmoid) and watch the signal flow forward.