MLPR FAQ, Autumn 2020
Responses to Frequently Asked Questions (FAQs).
- Should I take this course? Do I have the right background / know enough maths?
As stated on the main page, this course is intended as an introduction for those who want to move towards doing research in machine learning. If you are really interested in using machine learning, then IAML (MSc INFR11182; UG INFR10069) is a more appropriate choice.
If you do want to do research in this area, there are pre-requisites. Just because machine learning is popular you shouldn't ignore them. We've done what we can to outline what these pre-requisites are in the background section of the notes. If there are parts that you think we can improve, please provide feedback using the Hypothesis forum.
Ultimately you need to understand the course notes, so if the background notes don’t make sense, taking this course is probably a bad idea.
- Why is the course so hard?
MLPR isn’t an especially hard course — the mark average tends to be reasonable. However, the variance is large, which means more fail than we would like, and some of the best students complain it is too easy. MLPR assumes a reasonable level of mathematical experience. The level assumed isn’t unreasonable for a course in an Informatics department. For example, all of the undergraduates in this School study the maths that’s required, and the level of mathematical sophistication is probably less than most of the theory courses in the School and other excellent departments internationally.
- Why is the course so easy?
We're sorry if you find the course too easy. You will be in a small minority, but that won’t make it any less frustrating. There are pointers in the notes to material beyond the core material in the course. And we can try to provide more pointers if you make specific requests. Using Hypothesis, you can ask questions about any document that exists on the web, and you can also discuss anything you like in office hours. What you get out of the course is ultimately up to you.
- Will there be an exam?
In 2020, there will not be an exam after the course has finished. There will be a time-restricted class test to assess progress during the course.
- Will I cope with the programming?
We discuss the programming background that's required in the notes. You are expected to have some general programming experience. If you're not confident in Python, you will need to self-study a tutorial, and we advise you start now. Then, as long as you are diligent in trying the snippets in the notes, and the exercises we give you, you should be able to keep up.
Some people get in a mess with all the different types of array/list/matrix you can have in Python and Numpy. It takes experience to untangle this mess, and write neat code quickly. Reading examples isn’t enough, you’ll have to pull them apart, write your own, and debug your code.
An excellent way to get going quickly will be to get together with someone else in the class to try out code. Pair coding can work well remotely using screen sharing. It often prevents small slips that waste lots of time, and you rapidly learn things from other people that would take a long time to pick up any other way. If you are an expert programmer, you might learn even more through reflection during pair coding, and being able to guide others is an important skill in industry.
- Why do you use Hypothesis? Now I have to create a login
for yet-another tool / It doesn't work well on mobile / I'd rather just
use a normal forum.
Before using Hypothesis, MLPR used a similar annotation system called NB for several years. In surveys, a large majority of my classes consistently reported that they liked being able to ask questions directly on the notes. Partly they liked better feedback from instructors: questions attached to the notes are usually easier to answer, and directly help us to improve the notes.
In 2016 half a dozen annotation system alternatives were reviewed for MLPR, and Hypothesis (while not perfect) seemed the best option. It supports formatting (including code blocks) and maths, and has a better PDF viewer. Students used to make lots of request to upload extra documents to NB. With Hypothesis there is no need.
Hypothesis isn't perfect, and doesn't work well on mobile. Using a proper workstation is definitely preferable, which is probably true for a lot of your other course-related work too.
In previous mid-semester surveys a large majority (but not everyone) thought we should keep using Hypothesis. We will continue to consult; reasonable people will continue to have different opinions here.
- Can I get email updates from Hypothesis?
Hypothesis will email you when someone replies to one of your posts. However, they don't support emailing updates every time there is an update to a group. There are Atom and RSS feeds, which you could use to get updates. Also, we provide an optional email digest of all posts made by us.
Another suggestion is to plan your work in batches. If you schedule time to look over notes, including the Hypothesis stream, it may be more efficient than getting interrupted with notifications all the time.