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julia> using MNIST

julia> x, yy = traindata();

julia> n = length(yy)
60000

julia> y = zeros(10, n);

julia> for i in 1:n
           yi = yy[i]
           if yi == 0.0
               y[10, i] = 1.0
           else
               y[yi, i] = 1.0
           end
       end

julia> #x is 784 x 60000
       #y is 10 x 60000

julia> using NeuralNets

julia> layer_sizes = [size(x, 1), 30, size(y, 1)]
3-element Array{Int64,1}:
 784
  30
  10

julia> act = [logis, logis]
2-element Array{Function,1}:
 logis
 logis

julia> mlp = MLP(randn, layer_sizes, act);

julia> mlp1 = train(mlp, x, [], y, [], train_method=:levenberg_marquardt)
ERROR: MemoryError()
 in Array at base.jl:230
 in train at /home/sam/.julia/v0.3/NeuralNets/src/train.jl:66

julia> gdmtrain(mlp, x, y)
ERROR: `.+` has no method matching .+(::NNLayer{Float64}, ::Float64)
 in .+ at array.jl:758
 in gdmtrain at /home/sam/.julia/v0.3/NeuralNets/src/gradientdescent.jl:41

`setindex!` has no method matching setindex!(::ContiguousView{Float64,1,Array{Float64,1}}, ::Array{Float64,2}, ::UnitRange{Int64})

You might have used a 2d row vector where a 1d column vector was required.
Note the difference between 1d column vector [1,2,3] and 2d row vector [1 2 3].
You can convert to a column vector with the vec() function.
while loading In[8], in expression starting on line 21
 in backprop! at /home/sam/.julia/v0.3/NeuralNets/src/backprop.jl:39
 in backprop! at /home/sam/.julia/v0.3/NeuralNets/src/backprop.jl:35 (repeats 2 times)
 in g! at /home/sam/.julia/v0.3/NeuralNets/src/train.jl:93
 in fg! at /home/sam/.julia/v0.3/Optim/src/types.jl:150
 in gradient_descent at /home/sam/.julia/v0.3/Optim/src/gradient_descent.jl:56
 in optimize at /home/sam/.julia/v0.3/Optim/src/optimize.jl:328
 in train at /home/sam/.julia/v0.3/NeuralNets/src/train.jl:97