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Flux
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Version
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Home
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Where do I start?
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Installation
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Building Models
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Model Building Basics
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Model Templates
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Recurrence
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Debugging
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Other APIs
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Batching
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Backends
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Storing Models
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In Action
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Simple MNIST
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Char RNN
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Contributing & Help
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Internals
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< a class = "edit-page" href = "https://github.com/MikeInnes/Flux.jl/tree/957e23eb6bf488d698d1108678105bc26ba04798/docs/src/index.md" >
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Flux
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< em >
... Initialising Photon Beams ...
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Flux is a library for machine learning, implemented in Julia. In a nutshell, it simply lets you run normal Julia code on a backend like TensorFlow. It also provides many conveniences for doing deep learning.
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Flux is very flexible. You can use a convenient Keras-like API if you want something simple, but you can also drop down to straight mathematics, or build your own abstractions. You can even use Flux' s utilities (like optimisers) with a completely different backend (like
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< a href = "https://github.com/denizyuret/Knet.jl" >
Knet
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) or mix and match approaches.
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< p >
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Note that Flux is in alpha. Many things work but the API is still in a state of... well, it might change.
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< strong >
Note:
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If you' re using Julia v0.5 please see
< a href = "http://mikeinnes.github.io/Flux.jl/v0.1.1/" >
this version
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of the docs instead.
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Where do I start?
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< p >
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... Charging Ion Capacitors ...
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The
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< a href = "examples/logreg.html" >
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examples
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give a feel for high-level usage.
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< p >
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If you want to know why Flux is unique, or just don' t want to see
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< em >
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those digits
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again, check out the
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< a href = "models/basics.html" >
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model building guide
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instead.
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< p >
Flux is meant to be played with. These docs have lots of code snippets; try them out in
< a href = "http://junolab.org" >
Juno
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!
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< a class = "nav-anchor" id = "Installation-1" href = "#Installation-1" >
Installation
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< p >
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... Inflating Graviton Zeppelins ...
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< pre > < code class = "language-julia" > Pkg.update()
Pkg.add(" Flux.jl" )< / code > < / pre >
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< p >
You' ll also need a backend to run real training, if you don' t have one already. Choose from
< a href = "https://github.com/dmlc/MXNet.jl" >
MXNet
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or
< a href = "https://github.com/malmaud/TensorFlow.jl" >
TensorFlow
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(MXNet is the recommended option if you' re not sure):
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< / p >
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< pre > < code class = "language-julia" > Pkg.add(" MXNet" ) # or " TensorFlow"
Pkg.test(" Flux" ) # Make sure everything installed properly< / code > < / pre >
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Note:
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TensorFlow integration may not work properly on Julia v0.6 yet.
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Model Building Basics
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