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CRAN: Package fastai

fastai: Interface to 'fastai'

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 Documentation: Reference manual: fastai.html , fastai.pdf Vignettes: Basic Tabular (source, R code)
Audio Classification (source, R code)
Speech Recognition (source, R code)
Basic Image Classification (source, R code)
Bayesian Optimisation (source, R code)
Callbacks (source, R code)
Migrating from Catalyst (source, R code)
Custom Image Classification (source, R code)
Data augmentation (source, R code)
GPT2 (source, R code)
Head pose (source, R code)
Migrating from Lightning (source, R code)
Low-level ops (source, R code)
Medical image (source, R code)
Migrating from Ignite (source, R code)
Migrating from Pytorch (source, R code)
Multilabel classification (source, R code)
Object detection (source, R code)
Optimizer (source, R code)
Question-Answering (source, R code)
Super-Resolution GAN (source, R code)
RoBERTa (source, R code)
Text-summarization (source, R code)
Time-Series (source, R code)
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