Showing 5 of total 5 results (show query)
blmayer
deep:A Neural Networks Framework
This package provides a layer oriented way of creating neural networks, the framework is intended to give the user total control of the internals of a net without much effort. Use classes like PerceptronLayer to create a layer of percetron neurons, and specify how many you want. The package does all the tricky stuff internally leaving you focused in what you want. I wrote this package during a neural networks course to help me with the problem set.
Maintained by Brian. Last updated 5 years ago.
machine-learningneural-networks
6 stars 3.95 score 2 scriptsrcurtin
mlpack:'Rcpp' Integration for the 'mlpack' Library
A fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. See also Curtin et al. (2023) <doi:10.21105/joss.05026>.
Maintained by Ryan Curtin. Last updated 4 months ago.
3.71 score 20 scripts 8 dependentspaithiov909
baritsu:Wrappers for 'mlpack'
A collection of wrappers for the 'mlpack' package that allows passing formula as their argument.
Maintained by Akiru Kato. Last updated 1 months ago.
3 stars 3.08 score 1 scriptsandriyprotsak5
UAHDataScienceSC:Learn Supervised Classification Methods Through Examples and Code
Supervised classification methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in PK Josephine et. al., (2021) <doi:10.59176/kjcs.v1i1.1259>; and datasets to test them on, which highlight the strengths and weaknesses of each technique.
Maintained by Andriy Protsak Protsak. Last updated 2 months ago.
3.00 scorecomiseng
LearnSL:Learn Supervised Classification Methods Through Examples and Code
Supervised classification methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in PK Josephine et. al., (2021) <doi:10.59176/kjcs.v1i1.1259>; and datasets to test them on, which highlight the strengths and weaknesses of each technique.
Maintained by Víctor Amador Padilla. Last updated 2 years ago.
2.70 score 1 scripts