I don’t have the cash to build my own machine and that the weakest part for me is the proper build and use of an AWS EC2 instance for machine learning.
I really want to learn how to build an appropriate instance from scratch in order to gain a real understanding of what is going on … and I want to implement an instance that will support using Jupyter Notebooks against a Python 3, TF, Keras 2 technology stack in order to do the Kaggle competitions in this course.
So … can anyone recommend some good tutorials or walk-thrus?
The necessary steps are listed in the install-gpu.sh script - if you read through that, and update the steps for the versions you list, you’ll be up and running!
I see some discussion on folks going to Google Cloud but as I have $500 in credits for AWS … I’m going to stick with it and just want to setup a decent enough instance.
Is there any equivalent setup script for Windows-based computers already built?
UPDATE: I tried and mostly reached a working state. However, CUDA fails to compile any GPU code, because it requires Microsoft Visual Studio. That would not be a problem because I have it installed, but I believe it conflicts with the compiler used to build Anaconda, which seems to not be MSVC, rather gcc or gcc/mingw. There doesn’t seem to be any solution to this, and CUDA only supports MSVC on Windows. I will try to just disable GPU compilation, but there goes the whole point of trying to use my Windows workstation…
Thanks I’ve just added all regular forum users (anyone with >=1 like and >=2 posts) to the wiki and sent them an email with the login details. So that would be a great place to share your modifications!
(Sorry it’s taken me so long to get onto creating wiki logins!..)
Have you searched the forums on running the notebooks on a Windows machine?
I don’t have the links handy but I was able to piecemeal things together to get things running on my XPS 15 notebook using the 960 GPU. It was a tad painful but that is mostly because it was new to me. Definitely recommend going with a Linux build if possible, but Windows is doable. In fact, my development process right now is to do all my work on my PC with a sample dataset, check in everything to github … launch my EC2 instance, download my code from github, and run everything against the full datasets. Still learning and thinking about best approach to developing deep learning solutions … but this is working for me.
If you haven’t found the Windows links yet … lmk and I’ll dig them up.
At this point it’s a matter of principle so I want to have this working.
Running on AWS it’s much easier and faster, and I can see why it’s recommended though.