A Gentle Introduction To Sigmoid Function
Whether you implement a neural network yourself or you use a built in library for neural network learning, it is of paramount importance to understand the significance of a sigmoid function. The sigmoid function is the key to understanding how a neural network learns complex problems. This function also served as a basis for discovering other functions that lead to efficient and good solutions for supervised learning in deep learning architectures.
In this tutorial, you will discover the sigmoid function and its role in learning from examples in neural networks.
After completing this tutorial, you will know:
- The sigmoid function
- Linear vs. non-linear separability
- Why a neural network can make complex decision boundaries if a sigmoid unit is used