# 7.5: Deep Learning

Nowadays, “deep learning” is a bit of buzzword which used to designate software packages including multiple classification methods, and among the always some complicated neural networks (multi-layered, recurrent etc.) In that sense, R with necessary packages is a deep learning system. What is missed (actually, not), is a common interface to all “animals” in this zoo of methods. Package mlr was created to unify the learning interface in R:

Code $$\PageIndex{1}$$ (Python):

library(mlr)
...
## Specify the type of analysis (e.g. classification)
## and provide data and response variable
## 2) Define the learner, use listLearners()[,1]
## Choose a specific algorithm
lrn <- makeLearner("classif.ctree")
n = nrow(iris)
train.set <- sample(n, size=2/3*n)
test.set <- setdiff(1:n, train.set)
## 3) Fit the model
## Train the learner on the task using a random subset
## of the data as training set