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in AI and Deep Learning by (50.2k points)

This is a community wiki that aims to provide a good design for a machine learning/artificial intelligence framework (ML/AI framework).

Please contribute to the design of a language-agnostic framework which would allow multiple ML/AI algorithms to be plugged into a single framework which:

  • runs the algorithms with a user-specified data set.

  • facilitates learning, qualification, and classification.

  • allows users to easily plug in new algorithms.

  • can aggregate or create an ensemble of the existing algorithms.

  • can save/load the progress of the algorithm (i.e. save the network and weights of a neural network, save the tree of a decision tree, etc.).

What is a good design for this sort of ML/AI framework?

1 Answer

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by (108k points)

Possibly one can start by looking at the design of existing open-source ML/AI frameworks. To name a few: Weka, RapidMiner, KNIME, Orange.

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