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In this video from Sebastian Thrun, he says that supervised learning works with "labeled" data and unsupervised learning works with "unlabeled" data. What does he mean by this? Googling "labeled vs unlabeled data" returns a bunch of scholarly papers on this topic. I just want to know the basic difference.

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Unlabeled data consists of data which is either taken from nature or created by human to explore the scientific patterns behind it. Some examples of unlabeled data might include photos, audio recordings, videos, news articles, tweets, x-rays, etc. The main concept is there is no explanation, label, tag, class or name for the features in data.

Labeled data consists of unlabeled data with a description, label or name of features in the data. E.g. In a labeled image dataset, an image is labeled as it is a cat’s photo and it’s a dog’s photo.

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