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kindling  

Higher-Level Interface of 'torch' Package to Auto-Train Neural Networks
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("kindling", "0.3.2")



Attach the package and use:
library("kindling")
Maintained by
Joshua Marie
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-31
Latest Update: 2026-01-31
Description:
Provides a higher-level interface to the 'torch' package for defining, training, and tuning neural networks. This package supports feedforward (multi-layer perceptron) and recurrent neural networks (RNN (Recurrent Neural Networks), LSTM (Long Short-Term Memory), GRU (Gated Recurrent Unit)), and also reduces boilerplate code while enabling seamless integration with 'torch'. The methods to train neural networks from this package also bridges to titanic ML frameworks in R namely 'tidymodels' ecosystem, enabling the 'parsnip' model specifications, workflows, recipes, and tuning tools.
How to cite:
Joshua Marie (2026). kindling: Higher-Level Interface of 'torch' Package to Auto-Train Neural Networks. R package version 0.3.2, https://cran.r-project.org/web/packages/kindling. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-10 07:50), 0.1.0 (2026-01-31 19:40), 0.2.0 (2026-02-04 17:00), 0.3.0 (2026-03-03 07:00), 0.3.1 (2026-07-02 08:30)
Other packages that cited kindling R package
View kindling citation profile
Other R packages that kindling depends, imports, suggests or enhances
Complete documentation for kindling
Functions, R codes and Examples using the kindling R package
Full kindling package functions and examples
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