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Hands-on Machine Learning with R: An applied book covering the fundamentals of machine learning with R.
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01-introduction.Rmd
02-glm-models.Rmd
02-ml-strategy.Rmd
03-regularized-glm-models.Rmd
04-random-forest.Rmd
05-gradient-boosting-machines.Rmd
10-references.Rmd
README.md
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README.md

Hands-on Machine Learning with R

This repository is the home of the Hands-on Machine Learning with R book, which covers commonly applied supervised and unsupervised methods to include:

  • Generalized low rank models
  • Clustering algorithms
  • Autoencoders
  • Regularized models
  • Random forests
  • Gradient boosting machines
  • Deep neural networks
  • Stacking / super learner
  • and more!

See the online book at https://bradleyboehmke.github.io/hands-on-machine-learning-with-r/

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