The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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Updated
Jun 3, 2025 - Python
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The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Refine high-quality datasets and visual AI models
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.
📈 Adaptive: parallel active learning of mathematical functions
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 Convol…
Pool-based active learning in Python
Active learning for systematic reviews
MONAI Label is an intelligent open source image labeling and learning tool.
Active Learning for Text Classification in Python
The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.
Bayesian Optimization and Design of Experiments
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
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