Active Learning with AutoNLP and Prodigy
📰 Hugging Face Blog
Use AutoNLP and Prodigy to build an active learning pipeline for machine learning models
Action Steps
- Train a model using AutoNLP
- Use Prodigy to annotate and label data
- Retrain the model with the new labeled data
- Repeat the process to continuously improve the model
Who Needs to Know This
Data scientists and machine learning engineers can benefit from using AutoNLP and Prodigy to streamline their workflow and improve model accuracy
Key Insight
💡 Active learning with AutoNLP and Prodigy can improve model accuracy by iteratively adding labeled data and retraining the model
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🚀 Boost your ML model's accuracy with active learning using AutoNLP and Prodigy!
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