Neural Networks


3-Layer NN the scalar looks like this: where and are in the form of

  • can be a sigmoid, tanh, relu function

  • Hidden Nodes (hidden layer): perform computations and transfer input nodes to output nodes
  • Output Nodes (output layer): transferring information from the network to the outside world.
  • Connections and weights: each connection transferring the output of a neuron to the input of a neuron. Each connection is assigned a weight.
  • Activation function: non-linear function that defines the output of that node given an input or set of inputs

Types of Neural Networks

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