Neural Networks Basics

Understanding brain-like AI.

What are Neural Networks?

AI systems inspired by human brain.

Just like brain has neurons, neural networks have artificial neurons!

How They Work

Layers:

• Input layer (receives data)
• Hidden layers (process data)
• Output layer (gives answer)

Simple Example

Recognizing if image is a cat:

Input: Picture pixels
Hidden layers: Find patterns (ears, whiskers, fur)
Output: "Cat" or "Not Cat"

Neurons and Connections

Each neuron:

1. Receives input
2. Processes it
3. Sends output

Like passing a message through a chain of people!

Weights

Connections have weights (importance levels).

During training, weights adjust to improve accuracy.

Real Example

Face recognition in your phone:

• Takes your face photo
• Neural network processes
• Learns your unique features
• Unlocks phone when it sees you!

Deep Learning

Neural networks with many layers = Deep Learning

More layers = Can learn more complex patterns

Remember

• Neural networks mimic brain
• Made of layers and neurons
• Learn by adjusting weights