These instructions refer to this workshop event.
In this track we will use the R statistical software to perform simple data modelling.
In this track we will use Tensorflow and Python to build advanced machine learning and deep learning models.
Installing Tensorflow & Python on your laptop is optional. I will give you remote SSH access, during the workshop, to a server that has Tensorflow installed on it.
If you want to install Tensorflow on your laptop:
Summary of requirements if you install TF:
If you don't want to install Tensorflow on your laptop:
I will make my home tensorflow-ready server available to you during the workshop sessions. You'll just need an SSH client (I recommend Putty for Windows users, and the default ssh client for ubuntu/linux users) to access the server and run the jobs.
You should also install an SCP client (WinSCP for windows?) and an FTP client (I recommend FileZilla FTP client for windows). I haven't yet fully determined the means by which we'll transfer code and results, but I'm pretty sure it will be either scp and/or FTP, so you should make sure you can use both of these.
The way it will work is you will write up a python script on your laptop (or, if you're comfortable with command-line text editor tools like vim or nano, you can write the exercises directly on the server in your own folder), and then you will upload them to your folder on the server via either SCP or FTP (to be determined).
Then, you will use a script I made, that will queue up your job for execution as soon as the GPU is available. The output of your python script will be available in a .log file once executed by the queuing system. More specific instructions will be provided during the workshop itself.
Summary of requirements if you don't install TF: