@jpsamaroo Sure. That would be great help. It’s a very simple regression problem:

y=f(x_1,x_2,x_3,x_4,x_5,x_6)

The code is simple too:

```
using Flux
using Flux: throttle
using Base.Iterators: repeated
using Pkg
using DelimitedFiles
X_train = readdlm("X_train.txt", ' ', Float64)
y_train = readdlm("y_train.txt", ' ', Float64)
X_valid = readdlm("X_valid.txt", ' ', Float64)
y_valid = readdlm("y_valid.txt", ' ', Float64)
X_train = transpose(X_train)
y_train = transpose(y_train)
X_valid = transpose(X_valid)
y_valid = transpose(y_valid)
dataset = repeated((X_train, y_train), 5000)
m = Chain(Dense(6, 256, relu),
BatchNorm(256, relu),
Dense(256, 256, relu),
BatchNorm(256, relu),
Dense(256, 1, relu))
println(m)
loss(x, y) = Flux.mse(m(x), y)
evalcb = () -> @show(loss(X_valid, y_valid))
opt = ADAM(0.02)
Flux.train!(loss, params(m), dataset, opt, cb = throttle(evalcb, 10))
```