Sigmoid is the most common deep learning activation function. It’s an easy-to-implement smoothing function.
Sigmoidal comes from the Greek letter Sigma and plots as a sloping “S” on the Y-axis.
Sigmoidal function refers to any “S”-shaped logistic function, such as tanh (x). Unlike standard sigmoidal functions, tanh(x) exists between 1 and -1. A sigmoidal function is differentiable, therefore we can compute the slope at any two places.

  • https://insideaiml.com/blog/Sigmoid-Activation-Function-1031
  • Sigmoid is the most common deep learning activation function. It's an easy-to-implement smoothing function.
    Sigmoidal comes from the Greek letter Sigma and plots as a sloping "S" on the Y-axis.
    Sigmoidal function refers to any "S"-shaped logistic function, such as tanh (x). Unlike standard sigmoidal functions, tanh(x) exists between 1 and -1. A sigmoidal function is differentiable, therefore we can compute the slope at any two places.

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