Equations True Computer Science Geeks Should (at Least Pretend to) Know
1–10 of 100 posts
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#2The Y Combinator and the pumping lemma seem a bit contrived on that list, especially the former. I would add the maximum margin separation equation, which underlies many modern machine learning methods like SVMs and MMMF, and the P=NP equality question.
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#3It'd be nice if the author actually stated why these algorithms are important to know. Give a use case, rather than "this comes up sometimes."
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#4[deleted]
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#5This kind of list popped in HN a few weeks ago, almost the same stuff but with 10 equations.
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#6I would take issue with the pumping lemma for regular languages here. The formal statement of the lemma is outrageously complicated, which makes it really difficult to understand and use. The only good justification I’ve heard for including this result in a CS curriculum is that it’s a good warm-up for the pumping lemma for context-free languages, which is more useful.
If you actually ever find yourself needing to show that a particular language is non-regular, it’s almost always clearer to use an ad hoc argument or appeal to the Myhill-Nerode theorem. Actually the latter is much better, because Myhill-Nerode completely characterises the regular languages, whereas there are non-regular languages that pass the pumping lemma test.[1]
1. http://en.wikipedia.org/wiki/Pumping_lemma_for_regular_langu...
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#7The Y Combinator and the pumping lemma seem a bit contrived on that list, especially the former. I would add the maximum margin separation equation, which underlies many modern machine learning methods like SVMs and MMMF, and the P=NP equality question.
Understanding the pumping lemma is essential to really understanding why regular languages are limited. Which in the real world is important for quickly assessing the question of "can I hack this solution together with some clever regexps or do I need a real parser?"
I'll agree that the y-combinator is less essential, however if you even have a sense of what's going on it means that you have an understanding of the basic framework of functional programming and a minimal grasp of the lambda calculus
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#8I should think the Master Theorem would be included:
http://en.wikipedia.org/wiki/Master_theorem
or better,
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#9I really wish my brain didn't gloss over the first time I see a math symbol. All of this stuff seems intriguing but it's almost as if I'm hardwired to translate all those symbols into mush. I'd be much more interested in seeing the equivalent code snippets these ideas express.
Re: Equations True Computer Science Geeks Should (at Least Pretend to) Know
#10Since it seems like the multicore thing is here to stay, may I suggest that if you are doing anything parallel you should know about Amdahl's law: http://en.wikipedia.org/wiki/Parallel_computing#Amdahl.27s_l...