Name: Discrete Mathematics and Its Applications
ISBN: 9780073229720

Discrete Mathematics and Its Applications

Discrete Mathematics and its Applications, Sixth Edition, is intended for one- or two-term introductory discrete mathematics courses taken by students from a wide variety of majors, including computer science, mathematics, and engineering. This renowned best-selling text, which has been used at over 500 institutions around the world, gives a focused introduction to the primary themes in a discrete mathematics course and demonstrates the relevance and practicality of discrete mathematics to a wide a wide variety of real-world applications...from computer science to data networking, to psychology, to chemistry, to engineering, to linguistics, to biology, to business, and to many other important fields.

What Hacker News says

EzJBg4GSFeb 2022

I'm starting to learn CS all over again at the old age of 40, and had the pleasure to rediscover mathematics thanks to:

- Discrete Mathematics with Applications, by Susanna Epp, or

- Discrete Mathematics and Its Applications, by Kenneth Rosen (both have the same content, choose the style that you prefer), and

- Concrete Mathematics, by our lord and savior Donald Knuth.

I don't plan on reading TAOCP anymore as I would be dead by the time I finish reading everything else, but those introductory books are very good for beginners.

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cg30eNov 2021

For sure. I'll list some books for introduction to proofs, abstract algebra, real analysis, topology and category theory. These are not comprehensive, just listing books off the top of my head. I'll definitely be leaving off personal favorites other people have. You'll like some better than others. Some of these are beginner books and some are more advanced. A good tutor can help you get through the more advanced books. I tried to list the most beginner friendly book first in the list under each subject. Then the more advanced books later in the list.

Introduction to Proofs:

Just pick one of these that speaks to you the most. All three are good.

Discrete Mathematics with Applications - Epp

Discrete Mathematics and Its Applications - Rosen

Mathematical Proofs: A Transition to Advanced Mathematics - Chartrand, et al.

Abstract Algebra:

How to Think about Abstract Algebra - Alcock

Abstract Algebra - Pinter

Abstract Algebra: A First Course - Saracino

Algebra - Artin

Abstract Algebra - Herstein

Abstract Algebra - Dummit & Foote

Linear Algebra:

Maybe an engineering based book first if you haven't seen linear algebra in a while (e.g. Strang or Linear Algebra: Step by Step by Singh).

Then:

Linear Algebra - Friedberg, et al

Linear Algebra Done Right - Axler

Linear Algebra - Hoffman & Kunze

Real Analysis:

How to Think About Analysis - Alcock

Understanding Analysis - Abbott

Tao's Analysis text

Principles of Mathematical Analysis - Rudin

Topology:

Topology - Munkres

Topology A Categorical Approach - Tai-Danae Bradley, Tyler Bryson, and John Terilla

Check out this list:

http://pi.math.cornell.edu/~hatcher/Other/topologybooks.pdf for others.

Category theory:

Categories and Toposes: Visualized and Explained - Southwell

Conceptual Mathematics: A First Introduction to Categories - Lawvere

Category Theory for Programmers - Milewski (if you like functional programming)

Programming with Categories - Fong, Milewski, Spivak (if you like functional programming)

Category Theory in Context - Riehl

There are a few others by Spivak which you may like.

If you don't know category theory whatsoever then I like Southwell the best (pair them up with his youtube videos). Eugenia Cheng also has a nice set of lecture videos.

If you already know math pretty well, then Riehl is a favorite.

Hope that helps!

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mrbrowningOct 2019

To stick to the more theoretical interpretation of "computer science," and with a focus on theory of computation/programming languages:

- Discrete Mathematics And Its Applications, Kenneth H. Rosen (this is more foundational, but it's definitely targeted at a CS audience and touches on things like automata theory)

- Types and Programming Languages, Benjamin C. Pierce

- Semantics of Programming Languages, Carl Gunter

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jfaucettMar 2018

I've done exactly what you are talking about, so I think I have some insight that might be helpful.

For me, the biggest aid was finding good books, ones with exercises and that explained the material very well. Then it was just a matter of reading, actually doing all the exercises, and struggling with the material until I could fully understand it; then I moved on to the next chapter/book/etc.

I've worked through a lot of books by now but here's the short list of ones that I think are great for getting started(especially, if you do what I described above), also when these have solutions manuals I would advise getting them as well so you can ensure you understand how every problem works.

1. Calculus 4th ed. by Smith and Minton

2. Introduction to Linear Algebra (Gilbert Strang)

3. Introduction to Probability Theory (Hoel, Port, Stone)

4. Discrete Mathematics and its applications (Rosen)

5. Introduction to Automata Theory, Languages, and Computation (Hopcroft)

6. Introduction to Algorithms (Cormen, Leiserson, Rivest, Stein)

It will take you at least a year if not two to work through all these in your spare time, but the advantage is that after that you'll have the skills to be able to approach just about any topic in computer science (even highly theoretical ones) and not have much difficulty understanding them (at least that was my experience).

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kerneldeveloperApr 2017

I must recommend two books, both of them are awesome. One is Algorithm by Sedgewick and the other is The Algorithm Design Manual by Steven S. Skiena. You can read the first book and then the other. If you want some challenges and practice, try LeetCode and HackerRank. By the way, it'd be better to keep a discrete math book at hand, it would help you if you encounter some mathematical proof problems. I would recommend Discrete Mathematics and Its Applications by Kenneth H. Rosen for reference.

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bookrecDec 2016

Looking for recommendations on technical books that are written really well, where the form, flow, and structure – and not necessarily the content - are excellent.

Some examples that I enjoyed:

- SICP

- Discrete Mathematics and Its Applications

- K&R

- The C++ Programming Language

- Code: The Hidden Language of Computer Hardware and Software

- GEB

- Real-Time Rendering

- Artificial Intelligence: A Modern Approach

As a counter-example, some books that are considered classics or fundamental, and, in my opinion, don’t really shine in their style or structure:

- Deep Learning

- The Pragmatic Programmer

- Code Complete

- Introduction to Algorithms

There's a book series called The Best American Science and Nature Writing that I wholeheartedly recommend. Which books would you put in the shelf next to them?

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