I am trying to parallelize the code below. The idea is to run several model runs in parallel and push their output in to a single dataframe (i.e. dout). The code I have created works with no parrallelisation so far. However, I would be interested in making it faster as at the end I would have more than 1000 model runs. Any idea how I could parralelize this piece of code.
dout=DataFrame for i= 1:l10 model=train(y,x); ynew= predict(model, x[i) Prediction_df = DataFrame(Prediction=mapreduce(vec, vcat, ynew)) push!(dout,DataFrame(Prediction_df) end