Difference between Deep Learning and Machine Learning
Both deep learning and machine learning are subfields of artificial intelligence. But they have some core differences...
What is Machine Learning?
Machine learning is a subset of artificial intelligence that focuses on building systems that learn—or improve performance—based on the data they consume. It involves algorithms that can parse data, learn from it, and then apply what they've learned to make informed decisions.
What is Deep Learning?
Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to "learn" from large amounts of data.
Key Differences
Human Intervention
Machine learning requires more ongoing human intervention to get results. Deep learning is more complex to set up but requires minimal intervention thereafter.
Hardware Requirements
Deep learning programs require much more powerful hardware than machine learning programs.
Time
Machine learning models take less time to train but longer to test. Deep learning algorithms take a long time to train but very little time to test.
Approach
Machine learning tends to parse data in parts, while deep learning systems look at an entire problem or scenario in one go.