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Asked by Ashwini Last Modified
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Supervised learning uses labeled data (input-output pairs) to train a model, while semi-supervised learning uses a combination of labeled and unlabeled data, often improving performance by leveraging both types of information. It's like having some answers and trying to find more by using clues from the questions you don't know.
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How to learn Data Science?
I want to learn data science in home itself bcz i dont want much time to take any coaching and also most of the institutes are asking high amount for training. Pease lemme know how i can prepare myself.
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