This package has some very simple examples/tutorials for active learning to be as a set for building your own active learners

AL_Iris_SurveyPaper: This example is explained in the paper. This uses the iris dataset and using a simple active learner, one point is queried iteratively.
AL_IrisData_SurveyPaper: The same as AL_Iris_SurveyPaper, but using jupyter notebook to show the example in a step-by-step approach

AL_NumericalExample: This example is also presented in the paper, here few data points are used to trace the steps of the code easily
AL_NumericalExample (jupyter notebook of the AL_NumericalExample example)

ALMultiLayerNN4: This example explains how AL works with multi layer NN. Here, we used pytorch and MNIST dataset. The AL can select new points randomly or using one of the                      sampling algorithms.

DAL: This is deep active learning example. This example	explains how AL works with CNN (or deep learning generally). Here, simply AL selects the new points randomly or using         one of the sampling methods.

Plots: This script file has some functions that we used in our previous examples.

If the code is helpfull for you, please cite our paper:
Tharwat, A., & Schenck, W. (2023). A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions. Mathematics, 11(4), 820."
The link of the paper is here:
https://www.mdpi.com/2227-7390/11/4/820