Audience

Data scientists, AI developers, data labelers

About Prodigy

Radically efficient machine teaching. An annotation tool powered by active learning. Prodigy is a scriptable annotation tool so efficient that data scientists can do the annotation themselves, enabling a new level of rapid iteration. Today’s transfer learning technologies mean you can train production-quality models with very few examples. With Prodigy you can take full advantage of modern machine learning by adopting a more agile approach to data collection. You'll move faster, be more independent and ship far more successful projects. Prodigy brings together state-of-the-art insights from machine learning and user experience. With its continuous active learning system, you're only asked to annotate examples the model does not already know the answer to. The web application is powerful, extensible and follows modern UX principles. The secret is very simple: it's designed to help you focus on one decision at a time and keep you clicking – like Tinder for data.

Pricing

Starting Price:
$490 one-time fee
Pricing Details:
Per seat, available in packs of 5 seats

Integrations

API:
Yes, Prodigy offers API access

Ratings/Reviews

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Company Information

Explosion
Founded: 2016
Germany
prodi.gy/

Videos and Screen Captures

Prodigy Screenshot 1
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Product Details

Platforms Supported
Windows
Mac
Linux
Training
Documentation
Support
Online

Prodigy Frequently Asked Questions

Q: What kinds of users and organization types does Prodigy work with?
Q: What languages does Prodigy support in their product?
Q: Does Prodigy have an API?
Q: What type of training does Prodigy provide?
Q: How much does Prodigy cost?

Prodigy Product Features

Data Labeling

Labeling Automation
Task Management
Human-in-the-loop
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Team Collaboration
Training Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Templates
Visualization
Statistical / Mathematical Tools

Natural Language Processing

Sentence Segmentation
Tokenization
Stemming/Lemmatization
Part-of-Speech Tagging
Parsing
Named Entity Recognition
Co-Reference Resolution
In-Database Text Analytics
Open Source Integrations
Natural Language Generation (NLG)

Prodigy Additional Categories