I like this book. The probability section is great, especially how they handle the Monty Hall paradox. They use "four step method" that breaks it down perfectly - way clearer than the explanations you get in movies like 21 or numb3rs.
Mathematics for Computer Science (2018) [pdf]
31–40 of 69 posts
Re: Mathematics for Computer Science (2018) [pdf]
#32Anyway, this reminds me of a rather different initiative in the same vein: The building of Mathematical principles based on the expediences of Computer Science: CONCRETE MATHEMATICS
by Donald Knuth, Ronald Graham and Oren Patashnik.
https://www-cs-faculty.stanford.edu/~knuth/gkp.html
https://en.wikipedia.org/wiki/Concrete_Mathematics
available on the Internet Archive: https://archive.org/download/concrete-mathematics/Concrete%2...
Re: Mathematics for Computer Science (2018) [pdf]
#33I always see lists of like 100 MUST HAVE books for Computer Science. Is there like a top 5 must have books for Computer Science?
Re: Mathematics for Computer Science (2018) [pdf]
#34I always see lists of like 100 MUST HAVE books for Computer Science. Is there like a top 5 must have books for Computer Science?
Top 5 will never cover the field. Here's my top 10 * Brookshear and Brylow - Computer Science - An Overview * Forta - Teach yourself SQL in 10 minutes * Stallings - Computer Organization and Architecture * Stallings - Operating Systems - Internals and Design Principles * CLRS * Kurose, Ross - Computer Networking - A Top Down Approach * Sipser - Introduction to The Theory of Computation * Stallings, Brown - Computer S…
Over TCP/IP Illustrated?
Re: Mathematics for Computer Science (2018) [pdf]
#35Each section is quite standard in presentation which isn't a bad thing. I love that each citation has back references to _all_ the places that it is cited from. I wish more books did this.
Re: Mathematics for Computer Science (2018) [pdf]
#36I'm not such a fan of trying to cram everything-mathematically-relevant into a single huge book (and it is huge - 1048 pages). Anyway, this reminds me of a rather different initiative in the same vein: The building of Mathematical principles based on the expediences of Computer Science: CONCRETE MATHEMATICS by Donald Knuth, Ronald Graham and Oren Patashnik. https://www-cs-faculty.stanford.edu/~knuth/gkp.html https://…
Re: Mathematics for Computer Science (2018) [pdf]
#37This is why I love Hackernews - I've literally been looking for this recently and now I get it as a full PDF. Does anyone have recommendations for better screen readers?
Screen reader which is able to read PDF with Latex formulas? I will be surprised if this is possible at all. I can not even name most of the symbols from that formulae.
Re: Mathematics for Computer Science (2018) [pdf]
#38Earlier quoted context omitted.
I thought this thread was about computer science. Working on a programming project is related to computer science in the same way that welding together a shelf is related to mechanical engineering.
Being "handy" around the house (or even more advanced tinkering) and a mechanical engineering degree--maybe especially from a good school--are absolutely not the same thing.
Computer scientists often program but not all programmers are computer scientists.
Re: Mathematics for Computer Science (2018) [pdf]
#39I really love this book, it is hard af but I still can understand 1-2 pages of each paragraph. I have received some great insights, like the function is the endless lists of inputs and outputs, and some really great humour, such as all is not lost in mathematical notation. I really wish I can understand this book completely before I die.
"1-2 pages" Simplifying: -1 pages.
Re: Mathematics for Computer Science (2018) [pdf]
#40I find the well-ordering principle slightly bewildering. It seems to presuppose the existence of an ordering on natural numbers and then prove this principle. But I’ve never been taught things this way; you always construct the natural numbers from Peano and define the ordering first, then you can actually prove the well-ordering principle rather than leaving it as an axiom.