AI Foundations
Deep learning
A type of machine learning that uses many-layered neural networks to learn complex patterns.
Where it sits
Machine learning
Deep learning
Example
A photo app uses a many-layered neural network to recognize faces and objects.
Why it matters
It helps computers handle messy material where simple rules struggle to capture useful details.
You'll hear it
“The photo tool uses deep learning to recognize what's in the picture.”
Can you control it?
Set by the team
Model builders choose the network design, training data, and training settings. Most users cannot change whether an existing product uses deep learning.
Common questions
- Does adding more layers always improve results?
- No. Extra complexity can increase cost without improving the particular task.
- Why is deep learning used for images and language?
- They contain many stages that can build up useful patterns from complicated pictures or writing.
- Does deep learning require more data?
- Often yes. Large deep-learning systems commonly need more data and computing power than simpler approaches.