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Mathematics for Computer Science - Lecture Notes

ocw.mit.edu

21–27 of 27 posts

Re: Mathematics for Computer Science - Lecture Notes

#21
post #17

Earlier quoted context omitted.

Who are you to say that this doesn't matter for someone's development? This thread reads like you're trying to convince yourself that you don't need to understand this stuff.

I've taken quite a lot of university math courses. Not much is helpful for what I do in my development. In fact, not even the algorithms courses I've taken are all that helpful since most of the hard stuff is already done for you in libraries/frameworks.

to what I do in my development.

What I pointed out above is that there are people who do this stuff in their development. (-:

It seems like we're caught in this cycle where every 2 or 3 years, a new framework comes out that everybody rushes to embrace. Someone is writing the code to build these frameworks, and I guarantee you someone had to worry about what made their algorithm O(n^2) instead of O(log(n))

I think the reason you're being downvoted though, isn't because you simply pointed out that some people don't need to know this stuff, because (although somewhat pointless to state), that's true. Rather, I think the problem was when you said

Mathematics gets way more attention than it deserves in computing

Because you made no attempt to back it up, producing only evidence of your particular situation.

Re: Mathematics for Computer Science - Lecture Notes

#22
post #21

Earlier quoted context omitted.

I've taken quite a lot of university math courses. Not much is helpful for what I do in my development. In fact, not even the algorithms courses I've taken are all that helpful since most of the hard stuff is already done for you in libraries/frameworks.

to what I do in my development. What I pointed out above is that there are people who do this stuff in their development. (-: It seems like we're caught in this cycle where every 2 or 3 years, a new framework comes out that everybody rushes to embrace. Someone is writing the code to build these frameworks, and I guarantee you someone had to worry about what made their algorithm O(n^2) instead of O(log(n)) I think the…

It seems like we're caught in this cycle where every 2 or 3 years, a new framework comes out that everybody rushes to embrace. Someone is writing the code to build these frameworks, and I guarantee you someone had to worry about what made their algorithm O(n^2) instead of O(log(n))

The number of people working on difficult libraries/frameworks is rather small compared to the total number of developers.

Re: Mathematics for Computer Science - Lecture Notes

#23
post #17

Earlier quoted context omitted.

Who are you to say that this doesn't matter for someone's development? This thread reads like you're trying to convince yourself that you don't need to understand this stuff.

I've taken quite a lot of university math courses. Not much is helpful for what I do in my development. In fact, not even the algorithms courses I've taken are all that helpful since most of the hard stuff is already done for you in libraries/frameworks.

Do you not do anything algorithmic in your line of work?

Re: Mathematics for Computer Science - Lecture Notes

#24
post #21

Earlier quoted context omitted.

to what I do in my development. What I pointed out above is that there are people who do this stuff in their development. (-: It seems like we're caught in this cycle where every 2 or 3 years, a new framework comes out that everybody rushes to embrace. Someone is writing the code to build these frameworks, and I guarantee you someone had to worry about what made their algorithm O(n^2) instead of O(log(n)) I think the…

It seems like we're caught in this cycle where every 2 or 3 years, a new framework comes out that everybody rushes to embrace. Someone is writing the code to build these frameworks, and I guarantee you someone had to worry about what made their algorithm O(n^2) instead of O(log(n)) The number of people working on difficult libraries/frameworks is rather small compared to the total number of developers.

Many of those people read this site, however.

Re: Mathematics for Computer Science - Lecture Notes

#25
post #4

This is useful, but pretty standard undergrad material. There are more interesting OCW courses, such as Street Fighting Mathematics: This course teaches the art of guessing results and solving problems without doing a proof or an exact calculation. Techniques include extreme-cases reasoning, dimensional analysis, successive approximation, discretization, generalization, and pictorial analysis. Applications include me…

Note that the course's textbook, which is also called Street Fighting Mathematics, is available via Creative Commons Noncommercial Share Alike:

http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&#38...

Its a link on the left side under the picture.

Re: Mathematics for Computer Science - Lecture Notes

#26
post #4

This is useful, but pretty standard undergrad material. There are more interesting OCW courses, such as Street Fighting Mathematics: This course teaches the art of guessing results and solving problems without doing a proof or an exact calculation. Techniques include extreme-cases reasoning, dimensional analysis, successive approximation, discretization, generalization, and pictorial analysis. Applications include me…

Simple put: awesome

this reminds me of when I took partial differential equations where the instructor said: "this shit is really hard, so we are going to learn to guess the solution so we can even have a chance at getting close to the solution".

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