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Mathematics for Computer Science: Readings

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Re: Mathematics for Computer Science: Readings

#51
post #33

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?

There are a few reasons. First, the purpose of a class like this is to prepare students for further coursework in algorithms and automata/complexity. You need logic, graphs and combinatorics for those a lot more than you need linear algebra. Second, the math department teaches a class in linear algebra. This is a collection of topics that you wouldn't ordinarily find in undergraduate math classes. Third, there's a li…

> This is a collection of topics that you wouldn't ordinarily find in undergraduate math classes.

Much of this course is covered in undergraduate math classes, except at much greater depth (especially algebra and probability theory), and over the span of several courses.

Re: Mathematics for Computer Science: Readings

#52
post #44

Earlier quoted context omitted.

i agree with you that this is in principle math for CS proper (rather than machine learning or numerical algos or something) but >Second, the math department teaches a class in linear algebra. This is a collection of topics that you wouldn't ordinarily find in undergraduate math classes. x math department doesn't have classes on graph theory, combinatorics, or prob & stats?

At least in my school those were optional; only calc 1 & 2 and linear algebra were explicitly required, with combanatorics being commonly recommended but not required to grafuate

Blows my mind at times when I talk to a math major in the U.S. with little to no knowledge of graph theory. Also the abstract algebra exposure seems to be kind of restricted -- for instance Math 120 at Stanford (Groups and Rings) is highly suggested but not required.

Re: Mathematics for Computer Science: Readings

#53

Is this book suitable for math self-learning?

Yes.

Out of most math texts, this is very accessible and mind-expanding. Even if you don't get everything on the first pass, you'll come out with a lot of interesting insight into the field.

I don't know your level, but I don't recall anything too insurmountable for someone with a decent base in math.

Re: Mathematics for Computer Science: Readings

#54
post #35

Is this book suitable for math self-learning?

I took a look at the first four or so chapters and I'm not really a fan of the organization. But I think you could self-study the material and be fine. The introduction of the book explains that it's very focused on proofs, and it feels to me like it's more of an applied mathematics book than it is discrete mathematics (i.e. computer science) book. That's a subtle distinction, but I'd summarize it by saying this book…

I'm guessing you have a very strong math background if you are suggesting Concrete Math to a random person asking about self-teaching.

Concrete math requires MUCH more background than this book. Besides the real gems and clever tricks Mathematics for Computer Science appear after the fourth chapter.

Re: Mathematics for Computer Science: Readings

#55
post #35

Earlier quoted context omitted.

I took a look at the first four or so chapters and I'm not really a fan of the organization. But I think you could self-study the material and be fine. The introduction of the book explains that it's very focused on proofs, and it feels to me like it's more of an applied mathematics book than it is discrete mathematics (i.e. computer science) book. That's a subtle distinction, but I'd summarize it by saying this book…

I'm guessing you have a very strong math background if you are suggesting Concrete Math to a random person asking about self-teaching. Concrete math requires MUCH more background than this book. Besides the real gems and clever tricks Mathematics for Computer Science appear after the fourth chapter.

Really? What background do you think Concrete Mathematics needs?

Re: Mathematics for Computer Science: Readings

#57
post #45

Earlier quoted context omitted.

i agree with you that this is in principle math for CS proper (rather than machine learning or numerical algos or something) but >Second, the math department teaches a class in linear algebra. This is a collection of topics that you wouldn't ordinarily find in undergraduate math classes. x math department doesn't have classes on graph theory, combinatorics, or prob & stats?

You would not typically find dedicated undergraduate courses for graph theory, probability theory or combinatorics, no. At the very least you wouldn't expect to see those until you hit 300 level, but most likely not until graduate courses. Discrete mathematics is a grab bag of topics, and it's more fair to say that a discrete math course pulls in selected topics from other areas than to say it provides a focused cove…

Strange, I have taken a 4 credit, one quarter class in both probability theory and combinatorics in my undergraduate math and computer science education.

Re: Mathematics for Computer Science: Readings

#58
post #18

How has this book helped you as a programmer? I am finding it difficult going through it.

In my experience, it's been helpful occasionally. I've used techniques from it once or twice when writing algorithms to figure out what exactly the constraints on their inputs would be, however, other than that I don't think I've ever used it.

Re: Mathematics for Computer Science: Readings

#59
post #57
post #45

Earlier quoted context omitted.

You would not typically find dedicated undergraduate courses for graph theory, probability theory or combinatorics, no. At the very least you wouldn't expect to see those until you hit 300 level, but most likely not until graduate courses. Discrete mathematics is a grab bag of topics, and it's more fair to say that a discrete math course pulls in selected topics from other areas than to say it provides a focused cove…

Strange, I have taken a 4 credit, one quarter class in both probability theory and combinatorics in my undergraduate math and computer science education.

It is certainly possible to offer a complete class in combinatorics or probability theory at the undergrad level. The point is that such a course would cover far more than what a discrete math class would cover in those subjects.

Re: Mathematics for Computer Science: Readings

#60
post #35

Is this book suitable for math self-learning?

I took a look at the first four or so chapters and I'm not really a fan of the organization. But I think you could self-study the material and be fine. The introduction of the book explains that it's very focused on proofs, and it feels to me like it's more of an applied mathematics book than it is discrete mathematics (i.e. computer science) book. That's a subtle distinction, but I'd summarize it by saying this book…

Hi guys, thanks for the response. I think I will use this book for self-study and learn part that looks interesting for me.
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