Okay. So, the example code that I've put out on D2L, will run under Anaconda with Python 2.7. I have a Mac, and Mac comes with Scott BSD Unix under the hood. 2.7, 2.5 version of the installation of Python on a Mac is really, really slow. So, I went and got [inaudible] and it was better. Then I went and got Anaconda, and it is a tune Python for scientific computing and it's much, much faster, and then you get all these libraries as well. Has anyone using Anaconda before? Yes, few we have? Okay. For those of you who haven't, take a quick detour here, fired up. So, you're fired up and you get this kind of Launchpad desktop thing. The first one I want to show you is called Jupyter notebook. This is pretty slick because it runs in a web browser. So, clearly, there's a Python shell running behind this interface as presented in this web browser. But you can type Python code in these little cells. I think they're codes so you could say, for i in range five, colon, print i, then you go click on the little run button here, and it runs. That's how I started in all the examples except one are in these what's called this Jupyter notebook format. I was in a hurry when I was doing all my research for this segment, so I just did most of my stuff in these Python or these notebooks. But there's an editor in here, which is pretty slick. It's called the Spyder, and here's all the Python code for the logistic regression or linear regression example. The cool thing about this is, once you've run your code, you've got this variable explorer, says that no code has been written yet. So, the Python shell that's running underneath this hasn't seen any variable definitions. Yeah, but once you run the code, you can go click on all those variables and you can explore your dataset, and it's pretty handy. It's more useful I think than the Jupyter notebook. This book I was using also used R and I started to use R, but I was much more familiar with Python, and I just gave up trying to teach myself two things one at a time. Studying new Python, so I just took with Python and a lot of people and researchers use R, and then that comes down to personal preference, personal choice which you're comfortable with.