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R implementation for selected machine learning methods with deep learning frameworks (Keras, Tensorflow)
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tensorflow-wide-n-deep.R

README.md

deep-learning-recipes

Project Status: Active – The project has reached a stable, usable state and is being actively developed. License: MIT

R implementation for selected machine learning methods with deep learning frameworks (Keras, Tensorflow).

Principles: clean, self-contained, minimal dependency, works with the latest framework versions.

Contents

  • Triplet losses for implicit feedback recommender systems. [blog post] [code]
  • Matrix factorization for binary implicit feedback data. [blog post] [code]
  • "Wide and deep" model for regression/classification. [blog post] [code]
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