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Could someone tell what exactly is concept learning in Machine Learning?


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Concept learning in layman’s term is defined as the method of learning from examples. It infers Boolean valued function from its training examples as its input and output. Machine learning models are trained with a huge amount of data that helps it to classify different objects in different classes much like how humans deduce a piece of information based on past experiences.

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