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Mathematics for Computer Science: Readings

ocw.mit.edu

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Re: Mathematics for Computer Science: Readings

#11

Post by joker3 »

abhishekjha wrote: post #3
mikevm wrote: post #2

Latest edition of the book: https://courses.csail.mit.edu/6.042/spring18/mcs.pdf

I wonder how one would read 1000+ pages of a technical book like this.

Pencil in hand. When you see an argument whose steps you don't follow, work it out. When you get to the problems, do at least some of them. Follow the assignments in the MIT course, and check your work against the solutions.

Re: Mathematics for Computer Science: Readings

#13

Post by barronli »

mettamage wrote: post #9

Question: why isn't linear algebra in here? I know this is a type of "but this isn't in my favorite list" question but since a lot of universities include it in their CS curriculum, I wonder why it isn't in here. Or did I oversee it? Is in there?

I guess the book is more like “additional math for CS students beyond what a common CS curriculum has”.

Re: Mathematics for Computer Science: Readings

#14

Post by throwaway080383 »

mettamage wrote: post #9

Question: why isn't linear algebra in here? I know this is a type of "but this isn't in my favorite list" question but since a lot of universities include it in their CS curriculum, I wonder why it isn't in here. Or did I oversee it? Is in there?

Doesn't look like it.

One might argue that linear algebra is slightly more niche than stuff like graph theoretic algorithms. There are applications to broadly useful things like gradient descent, but that seems to fall under numerical linear algebra which probably deserves its own course in the Applied Math department.

N.b. just playing devil's advocate, I don't have a strong opinion either way.

Re: Mathematics for Computer Science: Readings

#15

Post by jjoonathan »

SebNag_ wrote: post #7
cultvoid wrote: post #6

Earlier quoted context omitted.

Some famous runner who's name I can't remember and probably didn't exist anyway once said "I can't run 200 miles. But I can run 1 mile - 200 times". Start from page 1 and iterate from there.

This analogy does not capture the problem that the human brain constantly forgets...

If you assume that "run 200 miles" doesn't refer to a single run but rather to the capability of running 200 miles, the analogy works much better. If you stop training the ability to run 200 miles vanishes even more quickly than an equivalent feat of learning.

Re: Mathematics for Computer Science: Readings

#16

Post by marpstar »

SebNag_ wrote: post #7
cultvoid wrote: post #6

Earlier quoted context omitted.

Some famous runner who's name I can't remember and probably didn't exist anyway once said "I can't run 200 miles. But I can run 1 mile - 200 times". Start from page 1 and iterate from there.

This analogy does not capture the problem that the human brain constantly forgets...

Sure it does. If you really wanted to read and understand this book and dedicated time each day to understanding 3 pages worth of content, you could read the book in a year. Remembering 3 pages of content per day (especially in math where concepts build on each other) is really not hard.

Re: Mathematics for Computer Science: Readings

#20

Post by mjlee »

mettamage wrote: post #9

Question: why isn't linear algebra in here? I know this is a type of "but this isn't in my favorite list" question but since a lot of universities include it in their CS curriculum, I wonder why it isn't in here. Or did I oversee it? Is in there?

Because 6.042J is "an introduction to discrete mathematics, probability, and mathematical thinking for computer scientists".

For linear algebra, see https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra...

I'll admit I don't know how the MIT CS curriculum is structured, but I suppose it is in there, just not in this particular course.

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