The Ultimate Big O Notation Tutorial (Time & Space Complexity For Algorithms)

do yourself a favor and play it at 0.75 speed

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What an amazing lad. Hope he reaches heights. thanks for the clear explanation

Very good! I just wish the video footage wasn't shaky!

Thank you!

very clear and on point

love you man...

Such a great and helpful video. You explained this sos well

This man doesn't use dots for bullet points he uses transmutation circles

Doesnt that make nlogn then 8 times 3 making it 24 as complexity????

Your videos have been really helpful to me and it seems like some of the things that trip me up sometimes also tripped you up as well.

Amazing content!

Watching this was fun. Thank you!

From the bottom of my heart, thank you so much for the gold knowledge

amazing energy and well explained. huge thanks!

Awesome teaching & white board also

wonderful!

Good explanations but camera is shaking too much !

Nah your whiteboards got whiteboards

"We can buy memory, but we can't buy more time." That's some deep stuff right there.

Out of the ones I checked out, this actually explains WHAT the concept is before jumping into some arbitrary code. Thanks!

Thank you! It helps me (a beginner) get a brief understanding of all those concepts in such an easy way.

good

bad camera work though

Bruh I need more practice on this! What can I do?

dude i love you

Love your energy bro! Thank you for your great explanations to so many concepts

Thanks for saving my life!

Oh gads, I want to watch this, this instructor seems very good but all the camera moving is making me feel ill. :( I hope you redo it sometime with the camera still on a base or something.

This is my question besides all this, plain English plain Math. int x = 3; right? O.K. what "operators" create more complexity? Do 2 operators on 1 line square the time? Each variable has a size in memory, int, char, float. so in PEMDAS notation per operator what creates complexity? I think I will make my own channel. thanks anyway for the try.

It forms what it look like a triangle--> Didn't understand this point for O(n2), how it formed a triangle?

it is unclear for me why the memory complexity is linear in fibonacci, since for each level we are making multiple calls/multiple stack allocations...

I find it interesting how you mentioned you can buy memory but you can't buy time. Can you not purchase faster CPUs? Why is it better to buy more memory than computational power?

Thanks!

what's his instagram? lol

so well prepared and planned, except for the camerawork lol

dude, stand still.... you make me confused... also, speaker, learn more about your topic before speak...

I just felt like i watched video at 2x speed. so much useful content in so less time.

Only thing missing is a tripod 🧐

too much information, with too much noise, too much movement,
I think this video needs to be made again!!

shaking camera and moving continues makes it hard to concentrate to topic unfortunately.

Never judge contents by video quality haha <3

i think you will need a new camera and cameraman...a better one of course

This video is one of the most complete and engaging i have seen

thank you!

Great one!!!!!!!!!

I almost vomit till space part. camera shaking too much. contents are good