In this project we concentrate on supervised learning.

'Classification of handwritten digits by matrix factorization'ĭeep learning can be used for both supervised and unsupervised learning. ORLMLDS Deep learning series (2): 'Using Keras with R (. Recording of the presentation at YouTube: (It was separated/extracted for clarity and convenience during the meetup presentation.) The slideshow is part of Sebastian Bodenstein's presentation at Wolfram U. 'Neural network layers primer' slideshow. H2O (that has interfaces to Java, Python, R, Scala.) See project's directory Remark: An alternative to R/Keras and Mathematica/MXNet is the library Remark: With 'deep learning with R' here we mean 'Keras with R'. 'Neural Networks in the Wolfram Language overview', ,Ĭan be used for a very fruitful comparison of features and abilities. WL's Neural Nets framework and abilities are fairly well described in the Some of Mathematica's notebooks repeat the material in. The focus of the talk is R and Keras, so the project structure is strongly influenced by the content Orlando Machine Learning and Data Science. The project is aimed to mirror and aid the talk

This MathematicaVsR at GitHub project is for the comparison of the Deep Learning functionalities in R/RStudio and Mathematica/Wolfram Language (WL).

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Mathematica for machine learning