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DeepAL is a Python library that implements various deep active learning algorithms, including Random Sampling, Least Confidence, and Bayesian Active Learning Disagreement. It requires dependencies such as PyTorch, NumPy, and scikit-learn, and provides a demo script for running experiments on datasets like MNIST.
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