TastyPancakes/Flux.jl
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

wording tweak

Browse Source
This commit is contained in:
Mike J Innes 2017-09-22 15:27:06 +01:00
parent f2052739c1
commit 96d1c55263
1 changed files with 3 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
docs/src/training/training.md
View File

@ -2,14 +2,14 @@
To actually train a model we need three things: To actually train a model we need three things:
* A *loss function*, that evaluates how well a model is doing given some input data. * A *model loss function*, that evaluates how well a model is doing given some input data.
* A collection of data points that will be provided to the loss function. * A collection of data points that will be provided to the loss function.
* An [optimiser](optimisers.md) that will update the model parameters appropriately. * An [optimiser](optimisers.md) that will update the model parameters appropriately.
With these we can call `Flux.train!`: With these we can call `Flux.train!`:
```julia ```julia
Flux.train!(loss, data, opt) Flux.train!(model, data, opt)
``` ```
There are plenty of examples in the [model zoo](https://github.com/FluxML/model-zoo). There are plenty of examples in the [model zoo](https://github.com/FluxML/model-zoo).
@ -23,6 +23,7 @@ m = Chain(
Dense(784, 32, σ), Dense(784, 32, σ),
Dense(32, 10), softmax) Dense(32, 10), softmax)
# Model loss function
loss(x, y) = Flux.mse(m(x), y) loss(x, y) = Flux.mse(m(x), y)
``` ```