Deep learning is a subset of machine learning that uses neural networks with many layers (that’s the deep part) to learn patterns from data. It’s the technology behind most of today’s impressive AI breakthroughs — image recognition, voice assistants, language models, and self-driving cars.
What Makes It Deep
Traditional machine learning uses simpler models with one or two layers. Deep learning uses networks with many hidden layers — sometimes dozens or hundreds — which allows it to learn increasingly complex representations of data. More layers means the ability to learn more abstract patterns.
Why Deep Learning Took Off
Deep learning has been around since the 1980s, but it exploded in the 2010s thanks to three things:
- Big data — massive datasets to train on
- GPU computing — graphics cards made training fast enough to be practical
- Better algorithms — improved training techniques and architectures
Key Applications
- Image and facial recognition
- Speech recognition and synthesis
- Language translation
- Medical diagnosis from scans
- Generating text (ChatGPT) and images (Midjourney)
Deep Learning for Website Builders
You probably won’t build deep learning models yourself, but they power most of the AI tools you’re using daily — from AI writing assistants to image generators to SEO tools.
Related: Neural Network
Related: Machine Learning
