Activation Functions
Learn about the most popular activation functions for deep learning.
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Activation functions are non-linear functions that determine the outputs of neurons. As we already discussed, each neuron accepts a set of inputs, multiplies them by the weights, sums them up, and adds a bias.
Because that will result in a linear transformation, we then pass neurons through a non-linear function so we can capture non-linear patterns between our data.
Over the years, many functions have been proposed, each one with its strengths and weaknesses. In this lesson, we will discuss the most common ones.
Sigmoid
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