A data pipeline framework for machine learning
Python
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fuel
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README.md

Fuel

Fuel provides your machine learning models with the data they need to learn.

  • Interfaces to common datasets such as MNIST, CIFAR-10 (image datasets), Google's One Billion Words (text), and many more
  • The ability to iterate over your data in a variety of ways, such as in minibatches with shuffled/sequential examples
  • A pipeline of preprocessors that allow you to edit your data on-the-fly, for example by adding noise, extracting n-grams from sentences, extracting patches from images, etc.
  • Ensure that the entire pipeline is serializable with pickle; this is a requirement for being able to checkpoint and resume long-running experiments. For this, we rely heavily on the picklable_itertools library.

Fuel is developed primarily for use by Blocks, a Theano toolkit that helps you train neural networks.