Input layer used in Artificial Neural networks each neuron represents a predictor variable.

In categorical variables, N-1 neurons are used when there are N number of categories. Input layer standardizes the range of the values by subtracting the median and dividing by the interquartile range. Then the input neurons feed the values to each of the neurons in the hidden layer.

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