neural network

A computational model inspired by biological neurons. Consists of layers of interconnected nodes that learn representations from data via backpropagation.

Syntax

ai-fundamentals

Input Layer -> Hidden Layers -> Output Layer
output = activation(weights * input + bias)

Example

ai-fundamentals

# Simple neural network with PyTorch:
import torch.nn as nn

class MLP(nn.Module):
    def __init__(self):
        super().__init__()
        self.layers = nn.Sequential(
            nn.Linear(784, 256),
            nn.ReLU(),
            nn.Linear(256, 10)
        )
    def forward(self, x):
        return self.layers(x)