What is Active Learning in Machine Learning?

Active learning is a type of machine learning where the algorithm is able to interactively query the user to obtain the most informative data points for training its model. The goal of active learning is to reduce the amount of data needed to train a model by focusing on the most important data points. This is done by allowing the algorithm to interactively query the user for labels or feedback on specific data points. This feedback can be used to identify the most informative data points for training the model. Active learning can be used to reduce the amount of labeled data needed to train a model, as well as to improve the accuracy of the model.