Since I couldn’t find a one-stop webpage covering all the instructions, I had to go back and forth multiple webpages. And then, after I’ve installed the whole thing, it took me a while to figure out how to run it.
And so, in this single post, I try to explain everything to you.
First up, I had to install the following packages:
- IPython Notebook
- GraphLab Create
GraphLab Create is not a free software, but they provide a 1-year, renewable license for educational purposes. You’ve to first go to their webpage and register yourself.
First up, go to the official instructions page and follow the instructions!
There are two options for installation:
- Installation into Anaconda Python Environment (recommended)
- Installation in Python environment using virtualenv
After following the official recommended path, you would have
- Installed Anaconda, pip, GraphLab Create, and IPython Notebook.
- Created a new Conda environment called
In case you’re wondering (like I did), rest assured that the Anaconda installation will not clash with your existing Python installation (that ships with most Linux distributions).
On their website there is an option to upgrade to a version that uses GPU acceleration. I haven’t tried that myself, but feel free to try it if you have a compatible GPU card.
Starting IPython Notebook to use GraphLab
The proper procedure for firing up the whole thing (in Linux) is:
- Open the terminal.
cdto the directory where your IPython Notebooks are.
Strictly speaking, this step is optional; but this is what you want to do in most cases.
- Activate the
gl-envConda environment which you created earlier (see below for a brief into to Conda).
$ source activate gl-env
- Start your IPython Notebook
$ ipython notebook
And there you go! You’re all set!
Step 3 above is where everybody gets it wrong; they simply skip this step! Although IPython Notebook would start up fine, if you skip step 3, python will choke at you when you try to import the
This is because, if you’ve followed the official instructions, only the
gl-env environment would have the
graphlab package installed.
Brief Introduction to Conda
Conda, in simple terms, is a tool that allows you to simultaneously have multiple installations of Python on your computer without messing up the different installations. ie., you could create different “environments” of Python, each with different packages.
Depending on your needs, you can set up the different “sandboxed” environments with different packages installed in them; even different versions of python itself! And you can easily switch between the environments. A prime advantage to working this way is that you don’t have to touch the native python installation on your OS (if it has one).
To learn more about using Conda, check out the official documentations:
Trust me, Conda makes your life so much easier.
Hope you’ve found this post helpful.
- GraphLab Create user guide
- GraphLab Create installation instructions
- GraphLab Create official website
- Download GraphLab Create for academic use
- Machine Learning Specialization on Coursera