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@data-programming

data-programming

Experimental and synthetic (fictitious) data sets for models of known and unknown phenomena.
  • Chicago, IL

Popular repositories

  1. model-to-data model-to-data Public

    Prepare a data set based on the model that you already have, then experiment with 'training' your 'Machine Learning' tool on this data. Did it recognize the model? Sorry, that was a stupid question…

    1 1

  2. fictitious-dimensions fictitious-dimensions Public

    Since the times of d'Alembert, Lagrange and Euler humans like to add fictitious dimensions to their real-world physical and mathematical problems. This art was perfected in the XX-th century by Hei…

  3. dataset-collection dataset-collection Public

    Forked from alxfed/dataset-collection

    Sources and Data Sets themself

Repositories

Showing 3 of 3 repositories
  • dataset-collection Public Forked from alxfed/dataset-collection

    Sources and Data Sets themself

    0 MIT 2 0 0 Updated Apr 29, 2018
  • fictitious-dimensions Public

    Since the times of d'Alembert, Lagrange and Euler humans like to add fictitious dimensions to their real-world physical and mathematical problems. This art was perfected in the XX-th century by Heisenberg, Pauli and Dirac in their 'matrix mechanics'. In the XXI-st century we can contribute to this proud tradition too, we have computers! :)

    0 0 0 0 Updated Apr 21, 2018
  • model-to-data Public

    Prepare a data set based on the model that you already have, then experiment with 'training' your 'Machine Learning' tool on this data. Did it recognize the model? Sorry, that was a stupid question. Why didn't it? You can find out with the help of these tools here.

    1 MIT 1 0 0 Updated Apr 20, 2018

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