diff --git a/src/Flux.jl b/src/Flux.jl
index d8db39e9..fb52e859 100644
--- a/src/Flux.jl
+++ b/src/Flux.jl
@@ -19,7 +19,7 @@ export Chain, Dense, Maxout, RNN, LSTM, GRU, Conv, CrossCor, ConvTranspose,
 include("optimise/Optimise.jl")
 using .Optimise
 using .Optimise: @epochs
-export SGD, Descent, ADAM, Momentum, Nesterov, RMSProp,
+export Descent, ADAM, Momentum, Nesterov, RMSProp,
   ADAGrad, AdaMax, ADADelta, AMSGrad, NADAM,
   ADAMW, RADAM, InvDecay, ExpDecay, WeightDecay,
   ClipValue, ClipNorm
diff --git a/src/optimise/Optimise.jl b/src/optimise/Optimise.jl
index 66be6dce..4ea5235e 100644
--- a/src/optimise/Optimise.jl
+++ b/src/optimise/Optimise.jl
@@ -2,10 +2,10 @@ module Optimise
 
 using LinearAlgebra
 
-export train!, update!,
-	SGD, Descent, ADAM, Momentum, Nesterov, RMSProp,
-	ADAGrad, AdaMax, ADADelta, AMSGrad, NADAM, ADAMW, RADAM, 
-	InvDecay, ExpDecay, WeightDecay, stop, Optimiser, ClipValue, ClipNorm
+export train!, update!, stop, Optimiser,
+		Descent, ADAM, Momentum, Nesterov, RMSProp,
+		ADAGrad, AdaMax, ADADelta, AMSGrad, NADAM, ADAMW, RADAM,
+		InvDecay, ExpDecay, WeightDecay, ClipValue, ClipNorm
 
 include("optimisers.jl")
 include("train.jl")
diff --git a/src/utils.jl b/src/utils.jl
index c666caca..7842c961 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -24,7 +24,7 @@ glorot_uniform(dims...) = (rand(Float32, dims...) .- 0.5f0) .* sqrt(24.0f0 / sum
     glorot_normal(dims...)
 
 Return an `Array` of size `dims` containing random variables taken from a normal
-distribution with mean 0 and standard deviation `(2 / sum(dims))`.
+distribution with mean 0 and standard deviation `sqrt(2 / sum(dims))`.
 
 # Examples
 ```jldoctest; setup = :(using Random; Random.seed!(0))