COMP61011 : Foundations of Machine Learning

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Maintained by G.Brown

How are the labs assessed?

There are no in-lab assessments. The sole practical assessment is a 6 page report, written as a team project (in teams of 2). For more details, read the handbook.

You are free to choose your own partner - please notify me by signing up here.

What language do we recommend and why?

The main language we recommend is Python and SciKit.Learn. This is now the main language used by data scientists and ML experts worldwide. If you wish to use another, you are free to do so. If you don't know Python, start with https://www.learnpython.org/. If you don't know SciKit.Learn, start with http://scikit-learn.org/stable/tutorial/basic/tutorial.html. If you want to install all this on your own machine, there's a good guide available here.

How do I start?

On Linux, type anaconda2 and then jupyter notebook. There may be some error messages that pop up depending on your system config, but just read them, and respond to what it says.

On Windows, start anaconda from the Run menu.

I highly recommend the SciKit Learn Cheat Sheet available here.