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fix some fences
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docs/src/models/quickstart.md

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@@ -53,7 +53,7 @@ mean((out2[1,:] .> 0.5) .== truth) # accuracy 94% so far!
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![](../assets/oneminute.png)
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```
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```julia
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using Plots # to draw the above figure
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p_true = scatter(noisy[1,:], noisy[2,:], zcolor=truth, title="True classification", legend=false)
@@ -81,7 +81,7 @@ Some things to notice in this example are:
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Instead of calling [`gradient`](@ref Zygote.gradient) and [`update!`](@ref Flux.update!) separately, there is a convenience function [`train!`](@ref Flux.train!). If we didn't want anything extra (like logging the loss), we could replace the training loop with the following:
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````julia
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```julia
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for epoch in 1:1_000
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train!(pars, loader, opt) do x, y
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y_hat = model(x)

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