Welcome to DFFML!

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Data Flow Facilitator for Machine Learning (DFFML) makes it easy to generate datasets, train and use machine learning models, and integrate machine learning into new or existing applications. It provides APIs for dataset generation, storage, and model definition.

  • Models handle implementations of machine learning algorithms. Likely wrapping code from a popular machine learning framework.

  • Sources handle the storage of datasets, saving and loading them from files, databases, remote APIs, etc.

  • DataFlows are directed graphs used to generate a dataset, as well as modify existing datasets. They can also be used to do non-machine learning tasks, you could use them to build a web app for instance.

You’ll find the existing implementations of all of these on their respective Plugins pages. DFFML has a plugin based architecture, which allows us to include some sources, models, and operations as a part of the main package, dffml, and other functionality in more specific packages.

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