How computationationally intensive is model making?


how computationally intensive is model making? do you use third party cloud computing services? Which ones and what are the cost and time?


It depends entirely on your model. A simple Logistic Regression can be run on a fairly standard laptop within a few seconds. The more complex models need more horsepower.

I’ve not looked into cloud computing solutions, but I suspect that you would have to be very good to make sure you get your money back by winning a round or two to offset the costs.


As @themicon stated, LR can finish running in few seconds. However running Deep Learning models is another story.
A single round of training, validation and test submission is around 20 minutes on my computer using PyTorch.
My specs are as follows:
Intel® Core™ i7–5930K CPU @ 3.50GHz, 64GB RAM, 1 GPU GeForce GTX 1080 with CUDA v. 8.0 (driver 375.20) and cuDNN (v. 5005) running on Linux.



Clustering and like-methods take a really long time. PRcomps in Microsoft R open takes about 0.1 seconds. I use h2o for most of the models and the slowest part is writing the data over to java. Even with the new data size the longest running model I have takes ~ 10 minutes, only because it does one each of all the favorite ML methods and finds optimal weights for a weighted sum. I could do this in parallel and it would take like 3 minutes. But we have all week, so no need.

I am actually doing this stuff on a newer i5. My point is, at this stage I dont know how necessary cloud is.