What is the difference between supervised and unsupervised learning ?

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In Supervised Learning the algorithm learns from labeled training data. In other words, each data point is tagged with the answer or the label the algorithm should come up with. Using such labeled data, the goal is to predict labels for new data points. The two common forms of supervised learning are classification and regression.

Unsupervised learning involves algorithms to analyze data without explicit target labels. The most common form of unsupervised learning is clustering where the aim is to group data to form cohesive clusters.  


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