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End-to-end machine learning on your desktop or server.

Project description

AIQC (wide)


📚  Documentation

🛡️  Community




End-to-end deep learning experiment tracking with tightly integrated pre & post processing.

On a mission to accelerate open science by making deep learning reproducible & accessible.


framework


  • Pipelines with tweakable parameters for data prep, model evalaution, and post-processing.
  • Achieve end-to-end reproducibility by recording every step in the process.


Thanks to the support and sponsorship of:


sponsor

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