Machine learning has been a common term for over a decade now. More and more we are seeing deep learning being used, and often interchangeably. This isn’t exactly correct. This interesting topic came to us from CTO Vision in their article, “Deep learning vs. machine learning: Understand the differences.”
Machine learning and deep learning are both forms of artificial intelligence (AI), but not identical. You could correctly say that deep learning is a specific kind of machine learning as both machine learning and deep learning start with training, test data, and a mode. Both can handle numeric (regression) and non-numeric (classification) problems, although there are several application areas where deep learning models tend to produce better fits than machine learning models.
The easiest way to think of their relationship is to visualize them as concentric circles with AI — the idea that came first, the largest; then machine learning which arrived later; and finally deep learning, which is driving today’s AI popularity — fitting inside both.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
