Active Learning
by Community · free · Last verified 2026-03-17
Selects the most informative unlabeled examples for human annotation using uncertainty sampling, query-by-committee, and expected model change strategies, minimizing labeling cost while maximizing model improvement. Reduces annotation budgets by 50-90% on benchmark tasks compared to random sampling.
https://modal.com/docs ↗B
B—Above Average
Adoption: B+Quality: AFreshness: ACitations: B+Engagement: F
Specifications
- License
- MIT
- Pricing
- free
- Capabilities
- uncertainty-sampling, query-by-committee, core-set-selection, batch-active-learning, stream-based-selection
- Integrations
- modAL, Small-Text, Label Studio, Prodigy, scikit-learn
- Use Cases
- NLP annotation budget reduction, Medical image labeling prioritization, Defect detection model bootstrapping
- API Available
- No
- Difficulty
- intermediate
- Prerequisites
- machine-learning, statistics, data-annotation
- Supported Agents
- Tags
- active-learning, data-labeling, annotation, query-strategy, low-resource
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
63.2Adoption
70
Quality
82
Freshness
80
Citations
75
Engagement
0