There are 40 repositories under active-learning topic.
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).
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.
A curated list of awesome Active Learning
MONAI Label is an intelligent open source image labeling and learning tool.
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
The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
Experimental design and (multi-objective) bayesian optimization.
Open source no-code system for text annotation and building of text classifiers
A web-based document annotation tool, powered by GPT-4 :rocket:
List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning
Tools for detecting wildlife in aerial images using active learning
Smarter Manual Annotation for Resource-constrained collection of Training data
Gaussian Processes for Experimental Sciences
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)