1.1 Amortized Analysis | Introduction with Examples | Advanced Data Structures | Algorithms

Подписаться 4,1 тыс.

Просмотров 78 тыс.

50% 1

In this video, I have explained amortized analysis with an example of augmented stack.
Next Video (Aggregate Method) : • 1.2 Aggregate Method |...
Tags:
#amortized #ammortized #advanceddsa #datastructures #dsa #introduction #augmentedstack #advanceddatastructures #cse #amortizedanalysis #timecomplexity #computerscience #it #algorithm #algorithms #software

Опубликовано:

2 окт 2024

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист

Посмотреть позже

Комментарии : 60

@IamNGD 2 года назад

After watching 20+ videos on this topic i found the one i really needed😢 thankyou so much sirji🙏

@uzairjavedakhtar3718 2 года назад

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 🙂

@IamNGD 2 года назад

@@uzairjavedakhtar3718 Sure sir🙏👍

@josedamiansanchez9874 Год назад

Great example explained to differentiate the Asymptotic and Amortized analysis.

@uzairjavedakhtar3718 Год назад

Haha! Had to think a lot before coming up with this😁 Thanks for taking out time to acknowledge it🖤

@ayushsuryawanshi9020 Год назад

Ofcourse Aman do better analysis than Asim

@siddheshshrirame6909 6 месяцев назад

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.

@uzairjavedakhtar3718 6 месяцев назад

Thanks a lot for your acknowledgement. Really means a lot🙂

@technohelper4855 2 месяца назад

I never comment .. but man this time I must say .. best explanation till now .. universities needs teachers like you

@uzairjavedakhtar3718 2 месяца назад

Thanks a lot for your kind words...Really means a lot :) If you really feel so, share it with your university students out there😉

@om7g.103 4 месяца назад

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

@mr.curious1329 2 года назад

Wonderfully explained.Compact and precise😃👍👍👍👍

@uzairjavedakhtar3718 2 года назад

Thanks for your kind words..Keep learning! And don't forget to share my channel😉

@vishvajithbalajee Месяц назад

hatsoff to your efforts sir, keep doing more videos on ADS.👍👍

@uzairjavedakhtar3718 14 дней назад

Sure. Thanks😊

@niharikasingh769 2 года назад

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.

@uzairjavedakhtar3718 2 года назад

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

@rho992 Год назад

Thank you that makes it clear..

@OODevelopers 7 месяцев назад

What are all the n+2 operations here?

@ur_fun Год назад

i hope, i will see u become one of the best teachers in utube. tanx a lot. keep it up

@uzairjavedakhtar3718 Год назад

Thanks A Lot for this beautiful comment😊 This really made my day🖤🖤🖤

@rho992 Год назад

Loved it... after watching so many video.. I can finally understand what we are actually even doing

@uzairjavedakhtar3718 Год назад

Really happy to know this 😊

@himankgaming7555 Год назад

6:20 i really though my earphone is gone before realising that the audio is like that BTW great explanation sir

@uzairjavedakhtar3718 Год назад

😂 Thanks😉

@ajinkyaawari575 Год назад

Best explanation through out whole internet 🔥🔥

@uzairjavedakhtar3718 Год назад

Now that's what I call the best comment through out whole internet😉

@evi5827 2 месяца назад

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!