2018-04-11 18:37:46 +00:00
< p align = "center" >
2018-04-25 10:51:58 +00:00
< img width = "400px" src = "https://raw.githubusercontent.com/FluxML/fluxml.github.io/master/logo.png" / >
2018-04-11 18:37:46 +00:00
< / p >
2016-03-22 19:58:58 +00:00
2019-04-25 11:04:03 +00:00
[](https://travis-ci.org/FluxML/Flux.jl) [](https://fluxml.github.io/Flux.jl/stable/) [](https://slackinvite.julialang.org/) [](https://doi.org/10.21105/joss.00602)
2016-12-15 21:08:43 +00:00
2018-03-16 12:22:30 +00:00
Flux is an elegant approach to machine learning. It's a 100% pure-Julia stack, and provides lightweight abstractions on top of Julia's native GPU and AD support. Flux makes the easy things easy while remaining fully hackable.
2016-04-01 21:11:42 +00:00
2017-09-11 13:54:30 +00:00
```julia
2019-11-28 16:00:21 +00:00
] add Flux
2017-09-11 13:54:30 +00:00
```
2017-09-11 13:56:35 +00:00
2019-04-25 11:04:03 +00:00
See the [documentation ](https://fluxml.github.io/Flux.jl/ ) or the [model zoo ](https://github.com/FluxML/model-zoo/ ) for examples.
2018-03-16 12:22:30 +00:00
2019-12-19 14:44:17 +00:00
If you use Flux in your research, please [cite ](CITATION.bib ) our work.
