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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.
Version: | 2.2.2 |
Imports: | reticulate, generics, png, ggplot2, ggpubr, glue |
Suggests: | knitr, testthat, rmarkdown, curl, magrittr, data.table, vctrs, stats, utils, R.utils, viridis, zeallot |
Published: | 2024-04-11 |
DOI: | 10.32614/CRAN.package.fastai |
Author: | Turgut Abdullayev [ctb, cre, cph, aut] |
Maintainer: | Turgut Abdullayev <turqut.a.314 at gmail.com> |
BugReports: | https://github.com/EagerAI/fastai/issues |
License: | Apache License 2.0 |
URL: | https://github.com/EagerAI/fastai |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | fastai results |
Package source: | fastai_2.2.2.tar.gz |
Windows binaries: | r-devel: fastai_2.2.2.zip, r-release: fastai_2.2.2.zip, r-oldrel: fastai_2.2.2.zip |
macOS binaries: | r-release (arm64): fastai_2.2.2.tgz, r-oldrel (arm64): fastai_2.2.2.tgz, r-release (x86_64): fastai_2.2.2.tgz, r-oldrel (x86_64): fastai_2.2.2.tgz |
Old sources: | fastai archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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