normalise(x; dims=ndims(x), ϵ=1e-5)

Normalise x to mean 0 and standard deviation 1 across the dimension(s) given by dims. Per default, dims is the last dimension. ϵ is a small additive factor added to the denominator for numerical stability.

Examples

			julia> using Statistics

julia> x = [9, 10, 20, 60];

julia> y = Flux.normalise(x);

julia> isapprox(std(y), 1, atol=0.2) && std(y) != std(x)
true

julia> x = rand(1:100, 10, 2);

julia> y = Flux.normalise(x, dims=1);

julia> isapprox(std(y, dims=1), ones(1, 2), atol=0.2) && std(y, dims=1) != std(x, dims=1)
true