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Author
Last Commit
Oct. 18, 2017
Created
Sep. 27, 2016

Embedded Learning Library

The Embedded Learning Library (ELL) allows you to design and deploy intelligent machine-learned models onto resource constrained platforms and small single-board computers, like Raspberry Pi, Arduino, and micro:bit. The deployed models run locally, without requiring a network connection and without relying on servers in the cloud. ELL is an early preview of the embedded AI and machine learning technologies developed at Microsoft Research.

Go to our website for tutorials, instructions, and a gallery of pretrained ELL models for use in your projects.

ELL is a work in progress, and we expect it to change rapidly, including breaking API changes. Despite this code churn, we welcome you to try it and give us feedback.

License

See LICENSE.txt.

Code of conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information on this code of conduct, see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Build and Installation Instructions

Technical Documentation

Latest Releases
v2.0
 Oct. 2 2017
v1.0
 Oct. 2 2017
v1.0
 Aug. 4 2017