NLPatl (NLP Active Learning)

This python library helps you to perform Active Learning in NLP. NLPatl built on top of transformers, scikit-learn and other machine learning package. It can be applied into both cold start scenario (no any labeled data) and limited labeled data scenario.

The goal of NLPatl is to make use of the state-of-the-art (SOTA) NLP models to estimate the most valueable data and making use of subject matter experts (SMEs) by having them to label limited amount data.

At the beginning, you have unlabeled (and limited labeled data) only. NLPatl apply transfer learning to convert your texts into vectors (or embeddings). After that, vectors go through unsupervised learning or supervised learning to estimate the most uncertainty (or valuable) data. SMEs perform label on it and feedback to models until accumulated enough high quailty data.

Installation

pip install nlpatl

or

pip install git+https://github.com/makcedward/nlpatl.git

Examples

• Quick tour for text input
• Quick tour for image input
• Quick tour for audio input
• Custom Embeddings, Classification, Clustering and Learning function

Release

0.0.3dev, Mar, 2022

• Support sci-kit learn extra library (Clustering)
• Support Nemo's speaker recognition embeddings layer

Citation

@misc{ma2021nlpatl,
  title={Active Learning for NLP},
  author={Edward Ma},
  howpublished={https://github.com/makcedward/nlpatl},
  year={2021}
}