invertiforms, covr, knitr, rmarkdown, testthat (>= 3.0.0)

c(
person('Turgut', 'Abdullayev', role = c('ctb', 'cre', 'cph', 'aut'),
email = 'turqut.a.314@gmail.com')
)
The 'fastai' <https://docs.fast.ai/index.html> library
simplifies training fast and accurate neural networks
using modern best practices. It is based on research
in to deep learning best practices undertaken
at 'fast.ai', including 'out of the box' support
for vision, text, tabular, audio, time series, and
collaborative filtering models.
reticulate, generics, png, ggplot2, ggpubr
knitr, testthat, rmarkdown, curl, magrittr, data.table,
vctrs, stats, utils

reticulate, generics, png, ggplot2, ggpubr, glue
knitr, testthat, rmarkdown, curl, magrittr, data.table,
vctrs, stats, utils, R.utils

knitr, testthat, rmarkdown, curl, magrittr, data.table,
vctrs, stats, utils, R.utils, nandb, viridis, zeallot

knitr, testthat, rmarkdown, curl, magrittr, data.table,
vctrs, stats, utils, R.utils, viridis, zeallot

A fast solver for constrained l1 minimization approach to sparse
precision matrix estimation
Haotian Pang, Han Liu and Robert Vanderbei
The package "fastclime" provides a method of recover the
precision matrix efficiently by applying parametric simplex
method.  The computation is based on a linear optimization
solver.

The package "fastclime" provides a method of recover the
precision matrix efficiently by applying parametric simplex
method.  The computation is based on a linear optimization
solver. It also contains a generic LP solver using parametric
simplex method.

A fast solver for parameterized lp problems and constrained l1
minimization approach to sparse precision matrix estimation
The package "fastclime" provides a method of recover the
precision matrix efficiently by applying parametric simplex
method.  The computation is based on a linear optimization
solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method.

A Fast Solver for Parameterized Linear Programming Problems and
Constrained L1 Minimization Approach to Sparse Precision Matrix
Estimation
An efficient method of recovering precision matrices
by applying the parametric simplex method is provided in this package.
The computation is based on a linear optimization solver.
It also contains a generic Linear Programming solver and a
parameterized Linear Programming solver based on the parametric simplex method.