Neural Network

A neural network is a type of machine learning model inspired by how the human brain works. It learns patterns from data and uses them to make predictions or decisions.

Basic Idea

A neural network is made up of layers of interconnected nodes (neurons):

• Input layer: takes in data (numbers, images, text, etc.)
• Hidden layers: process the data
• Output layer: gives the final result

Each connection has a weight, and each neuron applies:

• a weighted sum
• an activation function (like sigmoid, ReLU, tanh)

How It Works

Forward Propagation

• Input passes through layers
• Output is produced

Loss Calculation

• Compare output with expected answer
• Compute error

Backpropagation

• Error is sent backward
• Weights are adjusted to reduce error

Training

• Repeat many times → network “learns”