cure-lab/deep-active-learning
An implementation of the state-of-the-art Deep Active Learning algorithms
This project offers various strategies for 'active learning' with deep neural networks. It helps data scientists and machine learning engineers reduce the cost of labeling large datasets by intelligently selecting the most informative data points to be annotated. You provide a deep learning model and your unlabeled data, and it outputs a prioritized list of data points that will give the most bang for your buck in terms of labeling effort.
108 stars. No commits in the last 6 months.
Use this if you need to train a high-performing deep learning model but face high costs or time constraints for data labeling.
Not ideal if you already have abundant labeled data or if your problem doesn't benefit from deep learning models.
Stars
108
Forks
23
Language
Python
License
BSD-2-Clause
Category
Last pushed
Sep 19, 2023
Commits (30d)
0
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