DeepAL: Deep Active Learning in Python

Kuan-Hao Huang

DeepAL: Deep Active Learning in Python

Machine Learning 2021-12-01 v1

Authors: Kuan-Hao Huang

Abstract

We present DeepAL, a Python library that implements several common strategies for active learning, with a particular emphasis on deep active learning. DeepAL provides a simple and unified framework based on PyTorch that allows users to easily load custom datasets, build custom data handlers, and design custom strategies without much modification of codes. DeepAL is open-source on Github and welcome any contribution.

Keywords

software library compiler optimization

Cite

@article{arxiv.2111.15258,
  title  = {DeepAL: Deep Active Learning in Python},
  author = {Kuan-Hao Huang},
  journal= {arXiv preprint arXiv:2111.15258},
  year   = {2021}
}

Comments

project url: https://github.com/ej0cl6/deep-active-learning

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