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Active Learning in Machine Learning: Enhancing Efficiency and Accuracy

Machine learning algorithms have revolutionized the way we approach complex problems and make predictions. However, they heavily rely on labeled data for training, which can be a time consuming and expensive process. Active learning, a subfield of machine learning, aims to overcome this limitation by intelligently selecting the most informative instances to label, thus reducing the annotation effort while maintaining or improving the model's performance.