Комментарии:
A big thanks!
ОтветитьThank you so much!
ОтветитьGreat video
ОтветитьThank you and it is really helpful.
Ответитьi like the animation, how can i do something similar?
ОтветитьThe best video after spending hours I finally understood the big O!Thanks
ОтветитьYour explanation is bad
ОтветитьGet 2 pigeons
ОтветитьVery good, thanks. Please note that sometimes people pronounce O(1) as "order 1", O(n) as "order n", O(n^2) as "order n squared", etc.
ОтветитьYour green book explanation SUX compared to this video. Also you didn't cover the other Big O's.
ОтветитьIn rule 3 you told the (for b) inside (for a) loop should not be O(n^2) but O(a x b) but the same structure in rule 4 you wrote O(n^2)
Ответитьthank you! It really cleares stuff up :D
Ответитьthat pigeon analogy finally made it click for me.
ОтветитьVery nice video!
ОтветитьIve heard the pigeon story many times before, how couldnt i notice that 🤦♂
ОтветитьReally good explanation!
Ответить“DON’T BE LAZY!!!” is right. I was lazy for my Google interview because of the low stakes (I already have a job I am happy with) and fumbled almost every BigO question. It came up in every round. I knew which was faster intuitively, but found it hard to represent the correct notation. Learn this as it is very very important to fully grasp it. Also, know the BigO notations for most of the built in functions for your chosen language.
ОтветитьThis is a wonderfully clear explanation.
ОтветитьBigO
ОтветитьThere's a female teaching me how to code.
Ответитьma your big O looks like you wrote big D, you know, like ppenis
ОтветитьThis is what I needed to level up thank you soo much.
ОтветитьLovely video but surely you mean 'non-dominant' term. To dominate is to... well, you get the idea.
Ответитьcool
Ответитьgreat vid and explanation but please please use some normal font the next time
ОтветитьGood explanation. but texts are nearly unreadable because of the font :(
ОтветитьThe first rule contradicts the second one -if I have 2 loops 'a' and 'b' you are saying I need to add times -'a' +'b' , but then how come if I need to run SAME loop two times it is not 'a'+'a' but only 'a'??? I think first rule should be to take the longer loop: max(a,b). Your #1 rule is also contradicts to your #4 - dropping non-dominant terms.
ОтветитьWtf.....watched so many videos to understand this concept....and here u are explaining the same topic in an easy way...❤️❤️
Ответитьohh! Thank YOUUU
Ответитьрусская книга на столе
ОтветитьI appreciate the bird moving at the end. Fun touch.
ОтветитьHow could Big O be used for Covid data?
ОтветитьNice explanation. Very annoying voice.
ОтветитьI don’t understand why you have to use such huge vocabulary to explain this topic are you trying to prove something?
ОтветитьThats a great explanation , supercrisp and helpful for interviews .
ОтветитьIts kinda just like limits
ОтветитьI'm confused: If I iterate an array and also again per each item being read in the array I read again all the array, shouldn't it be O(a + a*b) or O(n + nn) ? (sorry I used nn instead of n square)
ОтветитьSuch a revolutionary explanation of Big O.
ОтветитьExcellent explanation! Thanks for simplifying Big O concepts.
ОтветитьGreat video, good theme the big O notation is very interesting
ОтветитьI loved the story as well as the explanation. I also knew the pigeon is going to win:-)
Ответитьso this vid was for time complexity not space complexity?
ОтветитьSo it's about how many times the function scales, and not how much time it takes to run
Ответить