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: | 2.0.1 |
| Imports: | reticulate, generics, png, ggplot2, ggpubr, glue |
| Suggests: | knitr, testthat, rmarkdown, curl, magrittr, data.table, vctrs, stats, utils, R.utils |
| Published: | 2020-11-12 |
| Author: | Turgut Abdullayev [ctb, cre, cph, aut] |
| Maintainer: | Turgut Abdullayev <turqut.a.314 at gmail.com> |
| BugReports: | https://github.com/henry090/fastai/issues |
| License: | Apache License 2.0 |
| URL: | https://github.com/henry090/fastai |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | fastai results |
| Reference manual: | fastai.pdf |
| Vignettes: |
Basic Tabular Audio Classification Speech Recognition Basic Image Classification Callbacks Migrating from Catalyst Custom Image Classification Data augmentation GPT2 Head pose Migrating from Lightning Low-level ops Medical image Migrating from Ignite Migrating from Pytorch Object detection Optimizer Super-Resolution GAN Time-Series |
| Package source: | fastai_2.0.1.tar.gz |
| Windows binaries: | r-devel: fastai_2.0.1.zip, r-release: fastai_2.0.1.zip, r-oldrel: fastai_2.0.1.zip |
| macOS binaries: | r-release: fastai_2.0.1.tgz, r-oldrel: fastai_2.0.1.tgz |
| Old sources: | fastai archive |
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