Prodigy ML

Prodigy ML

Prodigy ML is an annotation tool that helps train machine learning models faster. It allows users to rapidly label datasets and build accurate models with less data.
Prodigy ML image
machine-learning data-labeling computer-vision nlp

Prodigy ML: Rapid Machine Learning Model Training Tools

Prodigy ML annotation tool accelerates machine learning model training with fast dataset labeling and accurate model building, using less data.

What is Prodigy ML?

Prodigy ML is an efficient open-source data annotation tool for building machine learning models. It accelerates machine learning model development by making the data annotation process faster and more collaborative across teams.

Key features of Prodigy ML include:

  • Active learning suggestions to prioritize annotations for maximal model improvement
  • Pre-annotation with existing models to bootstrap new annotations
  • Real-time model evaluation as users annotate more data
  • Flexible interfaces including CLI, web app, and Python API
  • Seamless connections to train models in PyTorch, TensorFlow, scikit-learn, and other libraries
  • Team workflows for distributed annotation across annotators
  • Built-in datasets and recipes for common tasks like text classification, NER, image segmentation, etc

With Prodigy ML, machine learning teams can rapidly build accurate datasets, evaluate model performance in real-time, and continuously improve models - leading to faster development cycles and impactful model deployment.

Prodigy ML Features

Features

  1. Active learning to prioritize labeling
  2. Pre-built templates for common tasks
  3. Real-time model evaluation
  4. Team collaboration
  5. API access
  6. Integrations with popular ML frameworks

Pricing

  • Freemium
  • Subscription-Based

Pros

Speeds up model training

Reduces need for large labeled datasets

Intuitive interface

Works for image, text, audio and other data types

Cons

Limited free plan

Steep learning curve for advanced features

No offline usage


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