About this document
Activation Functions in Neural Networks by anupamabhan is a document available to read on EtoBox.
Activation functions in neural networks introduce non-linearity, enabling the model to learn complex data patterns. Various types of activation functions, such as Sigmoid, Tanh, and ReLU, each have unique properties that affect model performance, convergence speed, and gradient flow. The choice of activation function is crucial for effectively modeling real-world data and improving learning capabilities.
- Author
- anupamabhan
- Language
- EN