Unsupervised learning involves teaching an artificial intelligence (AI) algorithm with information that is neither classified nor labeled, and allowing this algorithm to respond to new information without supervision.
In unsupervised learning, the data provided to the AI system is not tagged or categorized, and the system algorithms process the data without any prior training. The output depends on the coded algorithms. The introduction into a system of an unsupervised learning approach is a great way to experiment with artificial intelligence.
Unsupervised learning algorithms can perform more complex processing tasks than supervised learning systems, but they can also be more unpredictable. Even if an unsupervised learning AI system can, for example, sort through cats and dogs, it can also add unexpected and unwanted categories to classify unusual breeds, creating confusion instead of putting things in order.
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