Active Learning Open Source Projects

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

A modular active learning framework for Python

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

Everything you need about Active Learning (AL).

Active learning for systematic reviews

Bayesian active learning library for research and industrial usecases.

ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

MONAI Label is an intelligent open source image labeling and learning tool.

Deep Active Learning

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

A curated list of awesome Active Learning

Pool-based active learning in Python

Curated list of open source tooling for data-centric AI on unstructured data.

INCEpTION provides a semantic annotation platform offering intelligent annotation assistance and knowledge management.

Active Learning for Text Classification in Python

🍳 Recipes for the Prodigy, our fully scriptable annotation tool

Bayesian Optimization and Design of Experiments

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

Experimental design and (multi-objective) bayesian optimization.

The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field

Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

Machine Learning for Computer Security

Open source no-code system for text annotation and building of text classifiers

A web-based document annotation tool, powered by GPT-4 :rocket:

Tools for detecting wildlife in aerial images using active learning

Gaussian Processes for Experimental Sciences

Smarter Manual Annotation for Resource-constrained collection of Training data

Reproducing experimental results of LL4AL [Yoo et al. 2019 CVPR]

A scalable & efficient active learning/data selection system for everyone.

A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)

active learning for accelerated high-throughput virtual screening

Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For the blog:

scikit-activeml: A Comprehensive and User-Friendly Active Learning Library for Reserach

NOVA is a tool for annotating and analyzing behaviours in social interactions. It supports Annotators using Machine Learning already during the coding process. Further it features both, discrete labels and continuous scores and a visuzalization of streams recorded with the SSI Framework.

🧬 A JupyterLab extension for annotating data with Prodigy

[IJCV] Bamboo: 4 times larger than ImageNet; 2 time larger than Object365; Built by active learning.

Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)

List of relevant resources for machine learning from explanatory supervision

Internet Explorer explores the web in a self-supervised manner to progressively find relevant examples that improve performance on a desired target dataset.

DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.

Awesome Active Learning Paper List

[CVPR'20] Implementation for the paper "ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation"

Multi-view face recognition, face cropping and saving the cropped faces as new images on videos to create a multi-view face recognition database.

[NPJ Com. Mat.] Offical implement of Bgolearn

AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging (ACL 2019 Demo)

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

[MedIA] Paper list and source code for survey "A comprehensive survey on deep active learning in medical image analysis"

Code for the EMNLP 2021 Paper "Active Learning by Acquiring Contrastive Examples" & the ACL 2022 Paper "On the Importance of Effectively Adapting Pretrained Language Models for Active Learning"

An implementation of the state-of-the-art Deep Active Learning algorithms

[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"

[CVPR 2024] Plug and Play Active Learning for Object Detection