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Framework for deep learning experiment tracking with tightly integrated data preprocessing.
On a mission to accelerate open science by making deep learning reproducible & accessible.
- 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:
