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What are the difference between supervised and unsupervised machine learning?

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Supervised learning is requires training labeled datas. For example, in order to the classification (a supervised learning task), you’ll need to the first label the data you’ll use to the train the model to classify data into your labeled groups. Unsupervised learning, in contrast, does not a require labeling data explicitly.

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Supervised learning - This model learns from the labeled data and makes a future prediction as output 

Unsupervised learning - This model uses unlabeled input data and allows the algorithm to act on that information without guidance.

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