AI Terminology
/Beginner
Input, Hidden & Output Layers
Definition
The architectural structure of a neural network. Data enters the Input layer, is processed by one or more Hidden layers, and the final prediction is produced by the Output layer.
Explain Like I'm New
Imagine a factory assembly line. Input Layer: The loading dock where raw materials (data) arrive. Hidden Layers: The factory floor where the workers (neurons) actually build the product. Output Layer: The shipping dock where the final product (the AI's guess) leaves the building.
Real World Example
An AI predicting house prices. The Input layer has 3 nodes (Bedrooms, Bathrooms, Zip Code). The Hidden layers do complex math to figure out how those relate. The Output layer has exactly 1 node (The predicted Dollar Price).
Common Use Cases
- •Network architecture
Interview Questions
basic
- Which layer is responsible for doing all the complex 'thinking' and pattern recognition in the network?
intermediate
- If an AI is classifying images of animals into 10 different species (Dog, Cat, Bird, etc.), how many neurons will the Output Layer have?