[Revised] Basic Theory of Neural Network

Last Updated on 15th July 2020 by Li-Wen Wang


In the document, we present:

  • Each neural network (NN) consists of many neurons, and each neuron has two elements: linear function and activation function.
  • We have shown the reason of using activation functions. (choices of activation functions)
  • Two numerical examples have been given to track the forward and backward propagation of a neuron.
  • We also implemented the NN to do binary classification task, and showed the experimental results.

Presentation Document

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