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I may be a troglodyte, but I was bored senseless in my linear algebra, calculus, discrete mathematics, statistics, etc classes in college. Then they tag all th

by hvs 9y ago

I may be a troglodyte, but I was bored senseless in my linear algebra, calculus, discrete mathematics, statistics, etc classes in college. Then they tag all the interesting stuff like AI (we didn't call it Machine Learning back in the 90s) at the end of your major where you actually use it. I had to go back and relearn it all because I didn't pay attention the first time. Note to mathematicians (or at least math professors): lead with the interesting stuff before the theory. It'll make learning easier and more fun.

Eridrus 9y ago
I'm basically in the same boat, except I thought our AI class was basically just A* and other forms of search and didn't go back to learning any of it until after university!
closeparen 9y ago
Same: I never gave a crap about algebra, or calculus, until AP physics. When I learned that the point (and the origin story!) of all this is to model the behavior of the universe I suddenly wished I had been paying attention for years prior. Seconding your wish that curricula would lead with motivations and then drill mechanics rather than drilling mechanics for 11 years and finally giving you the motivation in year 12.
colmvp 9y ago
It reminds me a bit of the motivation behind fast.ai, that you should get your hands dirty with the things you care about instead of learning the tough things until you're ready. I found it easier to learn things like stats, linear algebra, and calculus once I had a personal application to it. Even something that I love in Reinforcement Learning, I would sometimes get sleepy reading pages and pages from the Sutton and Barto book, but as soon as I worked on a coding exercise, I could spend hours actively participate with trying to solve the problem.
wolfgke 9y ago
> lead with the interesting stuff before the theory. It'll make learning easier and more fun. As a mathematician I say: What is considered as interesting is different for each person. I, personally, for example deeply love this really abstract stuff (but of course I am aware that other people have different preferences). So I would say even finding "interesting stuff" that many students in the lecture hall might be interested in is really, really hard. Another important argument against your idea is: To be even able to formulate the ideas from AI, one first have to learn and understand the words of the language in which one will formulate this. And these words are like "vector space", "linear map", "tensor product" etc. and understanding their meaning means knowing theorems about them. Starting with advanced topics, such as your AI example, is like giving beginner language learners a really advanced text in the foreign language that they just begin to learn. In other words: A reallz dubious idea. Considerung your post I can only ask you why you did not have a talk with the course advisor of your faculty. He would immediately have told you why these lectures are important for the things that you are actually interested in.

by hvs 9y ago

Eridrus 9y ago

I'm basically in the same boat, except I thought our AI class was basically just A* and other forms of search and didn't go back to learning any of it until after university!

closeparen 9y ago

Same: I never gave a crap about algebra, or calculus, until AP physics. When I learned that the point (and the origin story!) of all this is to model the behavior of the universe I suddenly wished I had been paying attention for years prior. Seconding your wish that curricula would lead with motivations and then drill mechanics rather than drilling mechanics for 11 years and finally giving you the motivation in year 12.

colmvp 9y ago

It reminds me a bit of the motivation behind fast.ai, that you should get your hands dirty with the things you care about instead of learning the tough things until you're ready. I found it easier to learn things like stats, linear algebra, and calculus once I had a personal application to it. Even something that I love in Reinforcement Learning, I would sometimes get sleepy reading pages and pages from the Sutton and Barto book, but as soon as I worked on a coding exercise, I could spend hours actively participate with trying to solve the problem.

wolfgke 9y ago

> lead with the interesting stuff before the theory. It'll make learning easier and more fun. As a mathematician I say: What is considered as interesting is different for each person. I, personally, for example deeply love this really abstract stuff (but of course I am aware that other people have different preferences). So I would say even finding "interesting stuff" that many students in the lecture hall might be interested in is really, really hard. Another important argument against your idea is: To be even able to formulate the ideas from AI, one first have to learn and understand the words of the language in which one will formulate this. And these words are like "vector space", "linear map", "tensor product" etc. and understanding their meaning means knowing theorems about them. Starting with advanced topics, such as your AI example, is like giving beginner language learners a really advanced text in the foreign language that they just begin to learn. In other words: A reallz dubious idea. Considerung your post I can only ask you why you did not have a talk with the course advisor of your faculty. He would immediately have told you why these lectures are important for the things that you are actually interested in.