jdagdelen/mondigy

A small component for using Mongodb databases with Prodigy annotation applications.

30
/ 100
Emerging

This tool helps data scientists and AI/ML engineers working with large text datasets efficiently prepare their data for machine learning. It allows you to pull unstructured text directly from a MongoDB database, perform human-powered annotations using Prodigy, and then store these labeled examples back into MongoDB. This streamlines the process of creating high-quality training data for natural language processing models.

No commits in the last 6 months. Available on PyPI.

Use this if you need to annotate text data stored in a MongoDB database using Prodigy and want to seamlessly integrate your annotation workflow with your existing NoSQL data storage.

Not ideal if your text data is stored in files, SQL databases, or other data sources not supported by MongoDB, or if you do not use Prodigy for your annotation tasks.

data-labeling text-annotation natural-language-processing machine-learning-engineering data-preparation
Stale 6m No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 25 / 25
Community 0 / 25

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Stars

9

Forks

Language

Python

License

MIT

Last pushed

Apr 20, 2021

Commits (30d)

0

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curl "https://pt-edge.onrender.com/api/v1/quality/nlp/jdagdelen/mondigy"

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