Active Learning

Active Learning is a machine learning technique that involves selecting the most informative data points from a large unlabeled dataset and requesting an expert to label them. The labeled data is then used to train a model, which is subsequently used to make predictions on new data. The process is repeated iteratively, with the model being retrained on the newly labeled data, until a satisfactory level of accuracy is achieved. Active Learning is particularly useful in situations where labeling data is expensive or time-consuming, as it allows the model to learn from a smaller amount of labeled data than would be required for traditional supervised learning techniques.
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