Activation Functions In Neural Networks Explained

Activation functions in neural networks are explored in this video, highlighting their definition, purpose, and various types, such as Step Functions, Sigmoid, TanH, ReLU, Leaky ReLU, and Softmax. The explanation includes how these functions are implemented in code, emphasizing their importance in transforming input signals within neural networks to introduce non-linearity, enabling the models to learn complex patterns.