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• v.1.1

  This milestone should provide gradient based optimization capabilities to the library, a new meta-heuristic algorithm named Gray Wolf Optimization, new readers for standard formats and CUDA implementation of benchmark test functions.

  Overdue by 5 year(s)

  •

  Due by June 1, 2020

  •1/4 issues closed
  25% complete3 open1 closed

• v.1.0

  This milestone will include the sequential and OMP version of standard benchmark functions, the inclusion of small and medium sized forecasting datasets and notebooks comparing sequential and OMP versions of standard functions and the accuracy of meta-heuristic training of a multi-layer perceptron and gradient based algorithms.

  Overdue by 6 year(s)

  •

  Due by March 1, 2020

  •3/8 issues closed
  37% complete5 open3 closed