Package: deepNN 1.2

deepNN: Deep Learning

Implementation of some Deep Learning methods. Includes multilayer perceptron, different activation functions, regularisation strategies, stochastic gradient descent and dropout. Thanks go to the following references for helping to inspire and develop the package: Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach (2016, ISBN:978-0262035613) Deep Learning. Terrence J. Sejnowski (2018, ISBN:978-0262038034) The Deep Learning Revolution. Grant Sanderson (3brown1blue) <https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi> Neural Networks YouTube playlist. Michael A. Nielsen <http://neuralnetworksanddeeplearning.com/> Neural Networks and Deep Learning.

Authors:Benjamin Taylor [aut, cre]

deepNN_1.2.tar.gz
deepNN_1.2.zip(r-4.7-any)deepNN_1.2.zip(r-4.6-any)deepNN_1.2.zip(r-4.5-any)
deepNN_1.2.tgz(r-4.6-any)deepNN_1.2.tgz(r-4.5-any)
deepNN_1.2.tar.gz(r-4.7-any)deepNN_1.2.tar.gz(r-4.6-any)
deepNN_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
deepNN/json (API)

# Install 'deepNN' in R:
install.packages('deepNN', repos = c('https://bentaylor1.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.36 score 23 scripts 342 downloads 22 exports 2 dependencies

Last updated from:424b1fb71c. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE105
source / vignettesOK161
linux-releaseNOTE104
macos-releaseNOTE117
macos-oldrelNOTE111
windows-develNOTE73
windows-releaseNOTE82
windows-oldrelNOTE79
wasm-releaseOK74

Exports:download_mnistdropoutProbshyptanidentL1_regularisationL2_regularisationlogisticmultinomialnbiasparnetworknnetparNNgrad_testNNpredictNNpredict.regressionno_regularisationQlossReLUsmoothReLUsoftmaxtrainwmultinomialwQloss

Dependencies:latticeMatrix