Today I worked on a presentation for the university Data Engineering course I’ve been tutoring this semester. I felt there was a bit of a gap in the course material. The first few lectures talk about types of data, experimental collection of data, basic statistics (such as mean, standard deviation, etc), plotting and presenting data, and fitting data (linear regression), and hypothesis testing.
And then the next lecture is a guest lecturer from MathWorks who comes in and talks about using MATLAB to do machine learning. It’s a large jump in complexity and depth of material, and I feel like many of the students are left a bit floundering like they’ve suddenly been thrown in the deep end. There’s no set up of the context or motivation for machine learning, or what it’s actually trying to do with the data.
Last lecture I spoke with the professor about this and he agreed with my idea of adding a bit of introductory context material to set up the machine learning content. We actually have an opportunity to deliver this because for the next three weeks we just have project sessions where the students show up to work in their teams and ask us questions if they need any guidance. We do the same thing in the Image Processing course in semester two, and there we’ve had a “bonus material” lecture at the start of one of those session. (Last year I did this, talking about the science and engineering of photography.)
So today I made a short presentation (just 9 slides), that we can give to the students on Monday. I set up the problem that we want to solve – classifying things by examining measurements—data—about them. I give examples to show how general this problem is and the wide range of important applications. Then explain why it can be difficult and how we can approach it in a data analytical way. And then how we can apply automated algorithms to do it in various different ways. Which leads into the machine learning examples that they did in the aforementioned previous lecture.
I tested it on my wife and it only took about 15 minutes. (And she now has a better understanding of the context of machine learning than most people!)
Also today I started work on writing a new batch of Irregular Webcomic! strips. I hope to get that done in time to photograph Lego on Tuesday morning.
The forecast rain hit today – it was much cooler than yesterday. But still we managed to set a new record for number of consecutive days in Sydney with maximum temperature 20°C or more. Looking at the Bureau of Meteorology records, it looks like 193 consecutive days – the last day we had a maximum below 20°C was 17 October, 2022. The forecast for every day in the coming week is at least 22°C, so the streak will probably extend past 200 days.
New content today: