Semi-Supervised Learning

Let's say you're learning to identify different types of trees. You start with a few trees that an expert has already identified for you. Using this knowledge, you then try to identify other trees on your own, even those you haven't seen before. This approach of learning with a mix of known (labeled) and unknown (unlabeled) examples is what we call 'Semi-Supervised Learning' in AI and ML.

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