Big O Notation, Time Complexity | DSA

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Опубликовано:

25 июн 2024

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Комментарии : 42

@malvernmabvira1562 10 месяцев назад

Can't be more grateful for this video🙏. Never seen a teacher like this.

@philjoseph3252 9 месяцев назад

You are the single greatest python teacher in the world, even Charles Severance can't teach as well as you. I watched so many videos on Big O but this is literally the first time I ever understood it

@asalkargauri2445 10 месяцев назад

thankyou so much sir i cant even express how you helped me by uploding this video i request you please complete dsa series thankyou somuch i owe you!!!!keep doing

@ajinzrathod 4 месяца назад

Keep up the good work! Please keep the DSA series on ongoing and also explain Time and Space Complexity in each of them. Your work is just AWESOME

@kapiljain7596 10 месяцев назад

Please post more videos like this. I understood the concept of big 0 very clearly

@AdarshaCoder 10 месяцев назад

I was waiting for this video... please keep uploading..

@gowthamreddysomala 10 месяцев назад

Meeru Great Teacher Sir..

@VivekSarmaKommanamanchi 8 месяцев назад

excellent video sir , we want more videos like these

@sankyaaaaa__ 10 месяцев назад

I want to say thank you for starting this dsa series....i was waiting for you to start dsa..the way you explain gets fit into the mind...

@rmpdasilva 10 месяцев назад

Really nice explanation!

@abdallahahmed6022 4 месяца назад

Sir you're the best. Thank you sooo much for your kind support!

@programmerdesire 10 месяцев назад

Amazing explanation ❤❤

@bharathtricks 10 месяцев назад

Thanks you so much sir it's very helpful ❤❤

@praveenmail2him 6 месяцев назад

Brilliant explanation!

@RajeshYadav-fz3ds 10 месяцев назад

Big thanks to Navin Annaya ❤ maja aayega

@sourishgupta3340 10 месяцев назад

More videos on algorithms and dynamic programming please, and help us to make better projects

@ghosal_mainak 10 месяцев назад

Hi Naveen If you can cover Dynamic Programming..it would be great help

@sanjaykushwah8271 9 месяцев назад

Thank you for the video; I learned a lot. However, based on your explanation in the video, I believe the O(n) graph should be positioned in the middle, not below.

@sarasalhi8 10 месяцев назад

thank you so much navin

@chuabenjamin 10 месяцев назад

Sir you are a hero

@GopiGopi-tl4vt 9 месяцев назад

Helpfull 🏅

@bharathtricks 10 месяцев назад

Super sir❤❤❤❤

@decimusmeridious4444 Месяц назад

thank you for existing

@touheedurrehman 10 месяцев назад

Thank you sir❤

@prashlovessamosa 10 месяцев назад

Good evening sir.

@iamdivyaprakash 10 месяцев назад

Good morning sir ! Are you going cover all DSA topics here ?

@OMKAR-lj8ci 7 месяцев назад

excellent

@runnysarfo4869 9 месяцев назад

can we use a binary search without sorting the array

@sohampaul1 5 месяцев назад

I have query in Binary search. As you said "if Target is less than the Mid value, then after Mid values of the array have no importance [8:37]". Why we count Mid value here for next loop ? We already know, Mid value is greater than Target value. It should be "if Target is less than the Mid value, then from Mid values of the array have no importance".

@radhakrishnabelievers Месяц назад

yes, u said correct, if the target is less the we move towards mid-1 will be the end point ,and if the target is greater then we move mid +1 will be the start point.

@rockstarkavya7431 26 дней назад

In binary search the numbers are always in ascending order

@rajivsharma7742 10 месяцев назад

Quite helpful 😇😇😇😇😇😇😇😇😇😇😇😇

@bahurudeen7 10 месяцев назад

Great Explanation sir❤🎉

@mahidhar6247 7 месяцев назад

nice

@mayuridhokane5493 10 месяцев назад

👍

@abdeldjalillouhichi1749 10 месяцев назад

♥♥

@zr0724 10 месяцев назад

sir thank you , please don,t ever skip this series or i will sucide 😩

@user-of8kt9no9s 4 месяца назад

sir even ChatGpt is recommending your channel

@rajeshpakkala 9 месяцев назад

Please start paid course or give full list of dsa sir

@gopichanti1977 4 месяца назад

In the following pseudocode, let A be an array of n positive integers, x be a positive integer number, start be an index, p be a list of integers, and result be a list of lists. a) Explain what the Mystery function does. b) Find an upper bound for its time complexity (T). Hint: You need to write T(n,x) as a recurrence relation and solve it by expanding it. function func(A, x): A.sort() result = [] Mystery(A, x, 0, [], result) return result function Mystery(A, x, start, p, result): if x == 0: result.append(p) return if x < 0: return for i from start to n - 1: Mystery(A, x - A[i], i + 1, p + [A[i]], result) anyone please help me with this ?