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 * Get Prodigy
 * Features
    * Named Entity Recognition
      Names, concepts and phrases
    * Span Categorization
      Overlapping and nested spans
    * Text Classification
      Label short and long texts
    * Dependencies & Relations
      Connect words and phrases
    * Computer Vision
      Classify and segment images
    * Audio & Video
      Label audio and video files
    * A/B Evaluation
      Fast and rigorous experiments

 * Documentation
 * Live Demo
 * Support

NavigationGet ProdigyFeatures   › Named Entity Recognition   › Span
Categorization   › Text Classification   › Dependencies & Relations   › Computer
Vision   › Audio & Video   › A/B EvaluationDocumentationLive DemoSupport


RADICALLY EFFICIENT MACHINE TEACHING.
AN ANNOTATION TOOL POWERED
BY ACTIVE LEARNING.

From the makers of spaCy
pip install ./prodigy.whl
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TRAIN A NEW AI MODEL IN HOURS

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.

How it works


THE MISSING PIECE IN YOUR DATA SCIENCE WORKFLOW

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.

Everyone knows data scientists should spend more time looking at their data.
When good habits are hard to form, the trick is to remove the friction. Prodigy
makes the right thing easy, encouraging you to spend more time understanding
your problem and interpreting your results.

Try the demo
Named EntitiesText ClassificationImagesFree-form

TRY IT LIVE AND HIGHLIGHT ENTITIES!

PERSON1ORG2PRODUCT3DATE4
In a March 2014 DATE×interview , Apple ORG×designer Jonathan Ive PERSON×used the
iPhone PRODUCT×as an example of Apple ORG×'s ethos of creating high - quality ,
life - changing products .


TRY IT LIVE AND SELECT TEXT CATEGORIES!

A US teenage TikTok user’s attempt to spread awareness about China’s oppression
of its Uighur Muslim population has renewed questions about censorship on the
China-based social media company’s platform.
Politics
1
Sports
2
Entertainment
3
Technology
4


TRY IT LIVE AND DRAW BOUNDING BOXES!

PERSON1SKATEBOARD2
All labels


BY: Kirk MoralesURL: unsplash.com/@knation


TRY IT LIVE AND TYPE SOME TEXT!

Tausende Menschen demonstrieren am Rande der 25. UN-Klimakonferenz für mehr
Klimaschutz.
Translation (German to English)


PRODIGY USERS INCLUDE

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TRY OUT NEW IDEAS QUICKLY

Annotation is usually the part where projects stall. Instead of having an idea
and trying it out, you start scheduling meetings, writing specifications and
dealing with quality control. With Prodigy, you can have an idea over breakfast
and get your first results by lunch. Once the model is trained, you can export
it as a versioned Python package, giving you a smooth path from prototype to
production.

Read more

WHAT OTHERS SAY


 * > ANDY HALTERMAN
   > 
   > @ahalterman
   > Mordecai would not have been possible without @explosion_ai's Prodigy. A
   > lack of labeled data held geoparsing back for years. It took a week to fix
   > that with Prodigy.


 * > FULLFACT
   > 
   > @FullFact
   > We've collected 25,000+ annotations from 90 fantastic volunteers, to
   > support our automated factchecking work thanks to Prodigy, an annotation
   > tool created by @explosion_ai.


 * > ANDREW TRASK
   > 
   > @iamtrask
   > I'm a huge fan of everything @explosion_ai does... they're brilliant... and
   > their new annotation tool is the best I've ever seen.


 * > LEVI DEHAAN
   > 
   > @levidehaan
   > ohhh snap I might have convinced my company to buy a bunch of licenses for
   > Prodigy by @explosion_ai woot! :D 🎵 I'm gonna train some models, I'm gonna
   > train some models 🎵 I'm going to have some fun :D


 * > RAPHAEL COHEN
   > 
   > @cohenrap
   > Prodi.gy is by far the best ROI we had on any tool!


 * > OLIVER BEAVERS
   > 
   > @oliverbeavers
   > just finishing up first major #nlp project with @explosion_ai's prodigy
   > active learning platform. in 3 hours, did what took > 10 volunteers,
   > painful google sheets nonsense, and weeks worth of time. game changer.
   > #yesimshilling


 * > DAVID CAMPION
   > 
   > @Orbis_21
   > “Text Classification: Be lazy, use Prodi.gy (a tool by @explosion_ai) !”.
   > This tool (prodi.gy) is fantastic and really help us to speed-up and build
   > our models.


 * > AJINKYA KALE
   > 
   > @ajinkyakale
   > Its amazing, every time i try to build something in house these guys beat
   > me at it providing an awesome solution out of the box!


FULLY SCRIPTABLE AND EXTENSIBLE

Prodigy is fully scriptable, and slots neatly into the rest of your Python-based
data science workflow. As the makers of spaCy, a popular library for Natural
Language Processing, we understand how to make tools programmers love. The
simple secret is this: programmers want to be able to program. Good developer
tools need to let you in, not lock you out. That's why Prodigy comes with a rich
Python API, elegant command-line integration, and a super productive Jupyter
extension. Using custom recipe scripts, you can adapt Prodigy to read and write
data however you like, and plug in custom models using any of your favourite
frameworks.

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recipe.pyimport prodigy
from prodigy.components.loaders import JSONL

@prodigy.recipe("custom")
def custom_recipe(dataset, source):
    return {
        "dataset": dataset,
        "stream": JSONL(source),
        "view_id": "classification"
    }


Command-line usageprodigycustommy_dataset./data.jsonl-F recipe.py

BROWSE FEATURES

 * 
   NAMED ENTITY
   RECOGNITION

 * 
   SPAN
   CATEGORIZATION

 * 
   TEXT
   CLASSIFICATION

 * 
   DEPENDENCIES &
   RELATIONS

 * 
   COMPUTER
   VISION

 * 
   AUDIO &
   VIDEO

 * 
   A/B
   EVALUATION


 * PRODIGY

 * Get Prodigy
 * Live Demo
 * Documentation
 * Support Forum
 * Terms & Conditions


 * FEATURES

 * Named Entity Recognition
 * Span Categorization
 * Text Classification
 * Dependencies & Relations
 * Computer Vision
 * Audio & Video
 * A/B Evaluation


 * EDUCATION

 * Documentation
 * Video Tutorials
 * Recipe Scripts
 * Example Projects
 * Support Forum

 * © 2017-2021 Explosion
 * Legal & Imprint
 * contact@explosion.ai
 * 
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