Supervised learning is part of artificial intelligence, big data, smart data and digital transformation. It refers to a method of machine learning in which computers learn from existing, already classified data.
Imagine you want to teach a computer to distinguish between photos of cats and dogs. To do this, you show it lots of pictures labelled as "cat" or "dog". The computer looks for patterns in these examples - such as the ears, the muzzle or the fur structure. As soon as enough examples have been processed, it can independently recognise new, unknown images.
Supervised learning is often used in everyday life, for example in the automatic detection of spam emails, in recommendations from online shops or in recognising fraud patterns in the financial sector.
The advantages: With this approach, the computer can take on many tasks where rules are difficult to define - it simply learns them from experience with existing data. Supervised learning is therefore a fundamental building block of modern applications within digital transformation and artificial intelligence.
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