https://github.com/slrbl/human-in-the-loop-machine-learning-tool-tornado

Tornado is an open source Human-in-the-loop machine learning tool. It helps you label your dataset on the fly while training your model through a simple web user interface. It supports all data types: structured, text and image.
https://github.com/slrbl/human-in-the-loop-machine-learning-tool-tornado

active-learning active-learning-module activelearning artificial-intelligence automl data-annotation data-annotation-machine-learning data-annotation-tools dataannotations human-in-the-loop-machine-learning interactive-machine-learning keras machine-learning machine-learning-api machinelearning natural-language-processing python ruby-on-rails sklearn

Last synced: 3 months ago
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Tornado is an open source Human-in-the-loop machine learning tool. It helps you label your dataset on the fly while training your model through a simple web user interface. It supports all data types: structured, text and image.

• Host: GitHub
• URL: https://github.com/slrbl/human-in-the-loop-machine-learning-tool-tornado
• Owner: slrbl
• License: agpl-3.0
• Created: 2019-01-19T22:54:30.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2023-04-15T04:52:25.000Z (almost 2 years ago)
• Last Synced: 2024-08-04T03:13:15.584Z (6 months ago)
• Topics: active-learning, active-learning-module, activelearning, artificial-intelligence, automl, data-annotation, data-annotation-machine-learning, data-annotation-tools, dataannotations, human-in-the-loop-machine-learning, interactive-machine-learning, keras, machine-learning, machine-learning-api, machinelearning, natural-language-processing, python, ruby-on-rails, sklearn
• Language: Ruby
• Homepage:
• Size: 150 MB
• Stars: 61
• Watchers: 2
• Forks: 10
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
TornadoAi
 

A zero coding human in the loop (HITL) collaborative data annotation plateform

What is TornadoAi

Tornado is an open source Human-in-the-loop machine learning tool. It helps you label your dataset on the fly while training your model through a simple web user interface. It supports all data types: structured, text and image.


Live demo

In this demo https://www.youtube.com/watch?v=zBe6b_vxs_I the user collaborates with the computer to label a set of 1300 pump impeller images through 4 human in the loop machine learning iterations. 

The goal of labelling the images is the put in place a classifier to automatize the metal casting quality process within a manufactory.




  


Data flow



Technology stack



Usage


Build Tornado Docker image

$ docker-compose build


Launch Tornado image

$ docker-compose up




Tornado will then be available at http://localhost:3000


Details and how to use

All information are available at:




https://www.linkedin.com/pulse/tornado-zero-coding-active-learning-ml-tool-walid-daboubi/