Create a visual lesson
~2 minDeep Learning vs. Machine Learning: What's the Difference?
Read the comparison below, or explore it visually. Create a visual lesson comparing deep learning and machine learning using available credits or plan allowance.
Deep learning is a specialized subset of machine learning. Machine learning is any system that learns patterns from data; deep learning is the branch that uses large, multi-layered neural networks to learn complex patterns — and it powers most modern AI breakthroughs.
At a glance
| Deep Learning | Machine Learning | |
|---|---|---|
| Relationship | A subset of machine learning | The broader field |
| Method | Many-layered neural networks | Many techniques, including deep learning |
| Data needs | Usually large datasets | Can work with smaller data |
| Features | Learns them automatically | Often needs hand-picked features |
| Powers | Image, speech, and language models | Spam filters, recommendations, forecasting |
Which should you use?
Deep Learning
Deep learning shines on complex, high-dimensional data — images, audio, language — given enough data and compute.
Machine Learning
Classic machine learning is often better for smaller datasets or simpler, structured problems, and is cheaper to run.
Frequently asked questions
Is deep learning the same as machine learning?
No — deep learning is a subset. All deep learning is machine learning, but machine learning also includes many simpler methods that don't use deep neural networks.
When is deep learning overkill?
For small datasets or simple, structured problems, classic machine learning is often faster, cheaper, and just as accurate — deep learning's edge shows with lots of complex data.
How do they relate to AI?
AI is the broadest term; machine learning is one approach to AI; deep learning is one approach to machine learning. Each is nested inside the last.