Neural Network Training

Every neuron in an artificial neural network can be seen as a mathematical function which, as a rule, connects several inputs to an output. From the input values, the neuron generates an output value that is passed on to the next layer of neurons. The higher this value is, the more “active” the neuron becomes in the network. This is why we refer to so-called activation functions. At this station you can try out how different mathematical functions in the neuron affect the output.

Source: https://ars.electronica.art/center/en/neuralnetworktraining/