Label Studio is a multi-type data labeling and annotation tool with standardized output format

Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Client interface for all things Cleanlab Studio

Segments.ai Python SDK

Code accompanying the TOP paper "Predicting the Demographics of Twitter Users with Programmatic Weak Supervision".

🚤 Label data at scale. Fun and precision included.

A curated list of awesome data labeling tools

A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.

A labeling interface for classifying old visualizations

A labeling interface for segmenting old visualizations

Toloka-Kit is a Python library for working with Toloka API.

Superpipe - optimized LLM pipelines for structured data

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

A Data Centric NER annotation tool for your Named Entity Recognition projects

A labeler-app for video labeling, for example for machine learning. For timewindows (|....|) and pointactivities (.|.)

Open source annotation tool for machine learning practitioners.

Make drawing and labeling bounding boxes easy as cake

An internationalized highly customizable annotation and evaluation tool for Natural Language Processing (NLP) tasks

A comprehensive NLP project using Azure AI Language service for custom text classification, integrated with Azure Blob Storage and containers. This project includes features for single-label classification, data labeling, and seamless model configuration through Language Studio, optimizing deployment efficiency.