2/15/2024 0 Comments Mathematica online compiler![]() ![]() The framework landscape was much simpler then, consisting of Torch, Theano, and Caffe, and a few less well-known frameworks such as MXNet’s progenitor CXXNet. In addition, the idea of building on top of an existing framework was very appealing: we could focus most of our efforts on writing the best possible high-level framework, and share the work of improving the low-level back end with a much larger community. ![]() We wanted to target a level of abstraction closer to wrappers like Lasagne (released 2014) or Keras (released March 2015) than Theano (the underlying framework on which Lasagne and Keras were built). In 2015, we at Wolfram decided to integrate a neural net framework into the Wolfram Language. The aim of this post will be threefold: to explain why MXNet was chosen as a back end, to show how the Wolfram Language neural net framework and MXNet can interoperate, and finally to explain in some technical detail how Wolfram Language uses MXNet to train nets that take sequences of arbitrary length (like the example above). Get a free trial today and find answers on the fly, or master something new and useful. Join the O'Reilly online learning platform.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |