Big-O Notation - For Coding Interviews

I'm feeling so stupid, man. Looks like w/o basic algebra knowledges, there is no way to understand this...

well explained my fried, you summarised two weeks worth of lectures in 20 minutes thanks for this

This guy is GOATed!

you're the best, thank you!

Thanks!

best BigO notation explanation period.

You are just Awesome!!!!

can someone explain? when to put n*m instead n^2. in my understanding, they are both the same but has different emphasis? i am correct?

Great content, ig while mentioning recursive algo having time comlexity O(c^n) you could have added that how after memoization we make it O(c.n)

I have a quiz in an hour and this helped SO much?? Thank you!

helpful

Bruh how do you explain things so well? Like seriously...not everyone who knows dsa has the potential to lay things out so easily. Your explanation has helped me a lot in many problems. Thanks a bunch man. Thanks a bunch.

thanks for the explanation!

this supposed to be a tutorial or a pep talk? so many concepts and terms introduced in like a min

so big o notation is just nested loop or not?

AAOA-DJRs alorithims N Log N , O(2^N)-O(9^N) utilising AAOA-DJRs.

Hi @NeetCode,
code NEET not working for lifetime access to all current & future courses. also, $169 from Bangladesh is very expensive, it's around 18500 BDT.

Great, but I believe factorial should be under exponential.

I can't open your site with code. Does it work?

Definitely interested in the "math stuff"!

You are an angel this was so helpful 🩷

simple and to the point. worth checking over and over

Love the way you explain things, so clear and creative and EASY to understand!!

anyone have any thoughts about: (N * M) vs (N log M) + (M log M)

example: (linear search through M-sized array N times) vs. (binary search through M-sized array N times + overhead of sorting M-sized array)

i'm guessing it's about the relative size of M and N, but i can't wrap my head around it

Thanks!

I was diving through out a lot of video and I just get it here really awesome explanation

What is heap? What happens when we heapify?

Hi NeetCode! Super video, thank you! I have a question: it's importanto for faang interview to have in your skills the analysis of the recurrence relation to retrive big o complexity in recursive functions? Thank you

We love you ❤️

I know nested loops are O(n**2) but would two loops iterating n elements be the same, or 2O(n**2) which would be reduced to O(n)?

👌

Which program do you use for your drawings?

Just great

damn this is a really good video. 20 min, and i understand it :)

Thank you for a great explanation of Big-O, very helpful! <3

Great content

Thanks

Sqrt time is used with prime and composite numbers calculations. It might be used in cryptography

Thanks

THANKS FOR GREAT EXPLANATIONS! I have become a sponsor of the channel now.

"if you're not smart enough or dont care"

I do care...
but I dont understand...
and I think im smart enough...

I will learn das math...

So well explained! Keep up the great vids!

Possibly the simplest way of explaining Big-O notations. Kudos.

You should at least mention amortized time. Beginners often ignore this idea and will e.g. use a map when it is really not needed, thinking that it is just as efficient as an array lookup because both are O(1). They should know that maps have more overhead and have an amortized cost, which makes them much less efficient than arrays in most cases. Pushing to a list is also amortized constant time.