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deepnet  

Deep Learning Toolkit in R
View on CRAN: Click here


Download and install deepnet package within the R console
Install from CRAN:
install.packages("deepnet")

Install from Github:
library("remotes")
install_github("cran/deepnet")

Install by package version:
library("remotes")
install_version("deepnet", "0.2.1")



Attach the package and use:
library("deepnet")
Maintained by
Xiao Rong
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-03-20
Latest Update: 2022-06-24
Description:
Implement some deep learning architectures and neural network algorithms, including BP,RBM,DBN,Deep autoencoder and so on.
How to cite:
Xiao Rong (2014). deepnet: Deep Learning Toolkit in R. R package version 0.2.1, https://cran.r-project.org/web/packages/deepnet. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.2 (2014-03-20 10:03)
Other packages that cited deepnet R package
View deepnet citation profile
Other R packages that deepnet depends, imports, suggests or enhances
Complete documentation for deepnet
Functions, R codes and Examples using the deepnet R package
Some associated functions: dbn.dnn.train . load.mnist . nn.predict . nn.test . nn.train . rbm.down . rbm.train . rbm.up . sae.dnn.train . 
Some associated R codes: dbn_dnn_train.R . dbn_train.R . load_mnist.R . nn_predict.R . nn_train.R . rbm_train.R . sae_dnn_train.R . sae_train.R . sigm.R .  Full deepnet package functions and examples
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