I hope you are not refering to My 20+ videos only😝 On a serious note, Thanks a lot for your appreciation. Means a lot🖤 If possible, please share the channel with your friends 🙂
tackling such important topics , which are not covered on whole youtube with such grace and lucid explanation is really praisable. Hats off to you sirji.
Didn't get one thing, in the second example: the asymptotic time complexity is for performing multipop n times which gives O(n^2) complexity but amortised complexity is for performing multipop(n) once and then pushing the elements back. This gives you O(n) complexity. But here also shouldn't we perform multipop n times. If we do that the time complexity will again be the same o(n^2). Basically my question is why we are not considering to perform multipop n times when finding amortised time complexity. I understand we don't have the elements left after 1st multipop but after pushing the elements back can't we perform multipop again and do it n times. Cause if it had to be done only once then even the asymptotic notation will give you O(n) complexity.
Great Question! You are raising this question because you are thinking that what I calculated in the video was the time complexity of the multipop(n) operation....Had that been the case, you are right But, that was instead the time complexity of the data structure. Now, what is the time complexity of any data structure? Suppose I give you a chance to perform n operations on a data structure and I tell you that what is the worst case time complexity you can prove in these n operations? So, if you are a Asymptotic fan, you would say that you will do multipop(n) n times( as it is the most expensive operation), which is not possible continuosly as your stack gets empty after each operation. But if you are doing Amortized analysis, you will still try to do worst case operations, i.e. multipop(n) ..but remember that u can just perform n operations...in that case, once u perform one multipop(n) operation, u cannot perform the other one until the n+2 th operation. So in total, how many multipop(n) u can do in n operations? Just 1 Hence , Time complexity for n operations comes out as O(n) If still any query, please ask 🙂 Kindly share the video
Why are the costs of TC1 O(n^2), when you multipop all n 1? wouldn't it be just one opertation of O(n), where the costs are O(1) for the whole stack? why multiply O(n) x n? Great video btw!
Amortized Analysis Aysmptotic Notation - Big O Notation , Big Theta Notation Why amortized analysis is more important than asymptotic notation in some cases An example Augmented Stack
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After watching 20+ videos on this topic i found the one i really needed😢 thankyou so much sirji🙏
I hope you are not refering to My 20+ videos only😝
On a serious note,
Thanks a lot for your appreciation.
Means a lot🖤
If possible, please share the channel with your friends 🙂
@@uzairjavedakhtar3718 Sure sir🙏👍
tackling such important topics , which are not covered on whole youtube with such grace and lucid explanation is really praisable.
Hats off to you sirji.
Thanks a lot for your acknowledgement. Really means a lot🙂
I never comment .. but man this time I must say .. best explanation till now .. universities needs teachers like you
Thanks a lot for your kind words...Really means a lot :)
If you really feel so, share it with your university students out there😉
Great example explained to differentiate the Asymptotic and Amortized analysis.
Haha! Had to think a lot before coming up with this😁
Thanks for taking out time to acknowledge it🖤
i hope, i will see u become one of the best teachers in utube. tanx a lot. keep it up
Thanks A Lot for this beautiful comment😊
This really made my day🖤🖤🖤
Best explanation through out whole internet 🔥🔥
Now that's what I call the best comment through out whole internet😉
Loved it... after watching so many video.. I can finally understand what we are actually even doing
Really happy to know this 😊
hatsoff to your efforts sir, keep doing more videos on ADS.👍👍
Sure. Thanks😊
Wonderfully explained.Compact and precise😃👍👍👍👍
Thanks for your kind words..Keep learning!
And don't forget to share my channel😉
Best video out here! Thanks
You are most welcome☺️
Didn't get one thing, in the second example: the asymptotic time complexity is for performing multipop n times which gives O(n^2) complexity but amortised complexity is for performing multipop(n) once and then pushing the elements back. This gives you O(n) complexity. But here also shouldn't we perform multipop n times. If we do that the time complexity will again be the same o(n^2). Basically my question is why we are not considering to perform multipop n times when finding amortised time complexity. I understand we don't have the elements left after 1st multipop but after pushing the elements back can't we perform multipop again and do it n times. Cause if it had to be done only once then even the asymptotic notation will give you O(n) complexity.
Great Question!
You are raising this question because you are thinking that what I calculated in the video was the time complexity of the multipop(n) operation....Had that been the case, you are right
But, that was instead the time complexity of the data structure.
Now, what is the time complexity of any data structure?
Suppose I give you a chance to perform n operations on a data structure and I tell you that what is the worst case time complexity you can prove in these n operations?
So, if you are a Asymptotic fan, you would say that you will do multipop(n) n times( as it is the most expensive operation), which is not possible continuosly as your stack gets empty after each operation.
But if you are doing Amortized analysis, you will still try to do worst case operations, i.e. multipop(n) ..but remember that u can just perform n operations...in that case, once u perform one multipop(n) operation, u cannot perform the other one until the n+2 th operation.
So in total, how many multipop(n) u can do in n operations? Just 1
Hence , Time complexity for n operations comes out as O(n)
If still any query, please ask 🙂
Kindly share the video
Thank you that makes it clear..
What are all the n+2 operations here?
Ofcourse Aman do better analysis than Asim
Why are the costs of TC1 O(n^2), when you multipop all n 1? wouldn't it be just one opertation of O(n), where the costs are O(1) for the whole stack? why multiply O(n) x n? Great video btw!
6:20 i really though my earphone is gone before realising that the audio is like that
BTW great explanation sir
😂
Thanks😉
Great explanation, thanks for sharing!
Thanks, Please share the channel with others :)
Amortized Analysis
Aysmptotic Notation - Big O Notation , Big Theta Notation
Why amortized analysis is more important than asymptotic notation in some cases
An example
Augmented Stack
Loved the explanation sir❤😊
😍
so to put it simply just look at the average? which is just O(1) because it happens most of the time
Yes that's the actual meaning of Amortized analysis ... Average time complexity of each operation
amazing explaination
Thanks 😊
Thank you so much, it was really helpful...
If it was helpful, it's worth it for me😊
Thanks for the appreciation🖤
Great explanation!
Glad to know that you liked it☺️
clear and understandable
Thanks😀😀😀 please share the channel if you liked it🙂
Thank you so much!!
You're welcome!☺️
why was it not 2n / n +1
Genuine doubt
And he saved me
🤩
next videos?
Entire playlist link : ruclips.net/p/PLv9sD0fPjvSHqIOLTIvHJWjkdH0IdzmXT
Thank you!
Most Welcome😊
Masth
Thanks A Lot Unnati :)
@@uzairjavedakhtar3718 please upload potential method as well
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