Understand Sigmoid Function: Properties and Derivative – Machine Learning Tutorial

By | September 21, 2020

Sigmoid function is often used as an activation function in neural network. In this tutorial, we will introduce the properties and derivative of this function.

What is sigmoid function?

The equation of sigmoid function is:

The equation of sigmoid function

The graph of sigmoid function is:

The properties of sigmoid function

There are some important properties, they are:

1. The value range

The value range of sigmoid function

2.

the properties of sigmoid function

The derivative of the sigmoid function

The derivative is:

The derivative of the sigmoid function

The graph of derivative is:

The graph of sigmoid function derivative

How to compute sigmoid value?

In tensorflow, we can use tf.sigmoid() function to compute the sigmoid value of a tensor. Here is the tutorial:

Compute sigmoid value of a Tensor with tf.sigmoid – TensorFlow Math Function

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