Overview

COMP 551, is your one-stop-shop for learning the fundamentals of Machine Learning (ML). In a single class, you will go from knowing nothing in ML to having a strong foundation in ML. We will go through the most utilized Machine Learning algorithms and you will code them from scratch without using any pre-existing libraries as if you invented them yourself.

But in order to achieve this very difficult feat, two things will be necessary. First, you will need to work very hard. Many students report needing to put in a huge amount of time and effort for COMP 551. Second, you need a very strong mathematical background to start with. Good knowledge of probabilities, linear algebra, and calculus is not optional. To check if you have the requisite math background, try to take this quiz. If you can complete this quiz easily, your math background is probably good, otherwise you should upgrade your math skills before taking COMP 551. We will also be coding in Python. So good knowledge of coding in Python is necessary. You can learn Python by taking COMP 202/204/208 before.

Don't be fooled by the "Applied" in the name "Applied Machine Learning". In COMP 551 we will go very deep into the math and theory of ML while also doing extremely hard, demanding, and time-consuming practical assignments. There are two very similar courses to COMP 551 which might be a better fit for you. ECSE 551 has very similar content but is possibly more applied. COMP 451 covers almost exactly the same content but being 3 credits instead of 4, it has a lighter workload.

The reward for successfully completing COMP 551 however, is that you will have strong ML foundation and you will be able to work independently in Machine Learning, whether that be in industry or for your research.

Please also have a look at the typical failure modes of students in COMP 551 HERE so as to prevent you also falling into one of those typical failure modes. Also notice the navigation side bar on the left. Please check out all the sections.

Welcome to COMP 551 ! We are super excited to have you join us on this Machine Learning journey.