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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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Digital Marketing vs Data Science: Which has a more fruitful career?
I want to get into data science but I dont have any prior knowledge on any of the programing languages, how do I go about it?
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