How to Choose an Activation Function for Deep Learning
Last Updated on January 19, 2021
Activation functions are a critical part of the design of a neural network.
The choice of activation function in the hidden layer will control how well the network model learns the training dataset. The choice of activation function in the output layer will define the type of predictions the model can make.
As such, a careful choice of activation function must be made for each deep learning neural network project.
In this tutorial, you will discover how to choose activation functions for neural network models.
After completing this tutorial, you will know:
- Activation functions are a key part of neural network design.
- The modern default activation function for hidden layers is the