Perceptrons and Layers

The perceptron is the simplest neural network - a single neuron. Understanding it unlocks neural networks.

The Perceptron

Activation Functions

Multi-Layer Networks

Key Takeaways

• Perceptron = single neuron, learns linear boundaries
• Activation functions: ReLU (most common), Sigmoid (output), Tanh
• Multi-layer networks can learn non-linear patterns
• More layers = more capacity but harder to train