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Flow-based data pre-processing for Machine Learning

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nuts-ml is a data pre-processing library for GPU based deep learning that provides common pre-processing functions as independent, reusable units. These so called ‘nuts’ can be freely arranged to build data flows that are efficient, easy to read and modify.

The following example gives a taste of a nuts-ml data-flow that trains a network on image data and prints training loss and accuracy

(train_samples >> Stratify(1) >> read_image >> transform >> augment >>
   Shuffle(100) >> build_batch >> network.train() >>
   Print('train loss:{} acc:{}') >> Consume())

nuts-ml is based on nuts-flow, which is described here.

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