Active Learning Toolbox

Spec sheet

Purpose

The repository provides active-learning query strategies, utilities, and a Jupyter dataset-annotation widget.Read 14 Nov 2026 · github.com

Support

The opened repository page does not state a support service or support response commitment.Read 14 Nov 2026 · github.com

License

The repository identifies its license as MIT.Read 14 Nov 2026 · github.com

Academic use

The README provides a citation for academic use and names a 2017 conference paper.Read 14 Nov 2026 · github.com

Annotation examples

The README links to examples for MNIST and 20 Newsgroups annotation.Read 14 Nov 2026 · github.com

Docker example

The README describes running example notebooks with Docker and opening the local Jupyter IDE.Read 14 Nov 2026 · github.com

Installation

The repository instructs users to install the library and widget from GitHub using pip.Read 14 Nov 2026 · github.com

Integration

The project says it has tight integration with the LibAct Python library.Read 14 Nov 2026 · github.com

Jupyter setup

Jupyter widgets need to be installed and enabled separately according to the README.Read 14 Nov 2026 · github.com

Package maturity

The repository states that Python versions earlier than 3.6 have not been tested.Read 14 Nov 2026 · github.com

Requirements

The listed requirements include Python 3.6, NumPy, pandas, scikit-learn, SciPy, Pillow, Jupyter, and a LibAct fork.Read 14 Nov 2026 · github.com

Workflow

Its described workflow has experts label selected examples, train a classifier, and add further selected examples to its training set.Read 14 Nov 2026 · github.com

Plans and prices

Every Active Learning Toolbox plan and price →

Where Specifiction places it

• Active Learning Tools#2 of 168.1