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Thank you so much for the great explanation.

sir can you mention the source of the lecture ..like which book is it plz.

4:30 - Assembly Line Scheduling

its was amazing concepts Thank Dr.✍✍✍✍

Why no buddy can do backtrack properly 😑

This is the best video I have seen on this topic

Dr. Hasan Jamal, do we need to check Omega(n^log_b{a} + epsilon) ? So we set in Omega 1+e, so for example e=0.1. and we check it if 2 = 1.1 ? Nope 2>1.1 ? I have understood if we compare f(n) with omega ^ 1 + e

Best video. Looking forward to watch more videos of DS of him

Great Video! I am currently writing my bachelor thesis over bin-packing, could you recommend any literature ? wishes from germany

thank you sir

how do we know when to use theta or when to use big omega? at 14:05 can't it be theta(n^2)?

Great video

Sir can you please make more videos of ADA

Sir how is addition going on i am confused on how hm traverse kr rhei like hr station k lie shuru se again count krna prega ?

Sir how is addition going on i am confused on how hm traverse kr rhei like hr station k lie shuru se again count krna prega ?

Very good lecture, thanks.

sir could u provide the channel link for all the content regarding algorithms.

The 5th example is not correct, we can assume the tree’s short end is extend to long end and get T(n)<=nlog(3/2)(n) And cut long end of the tree to align with the short end then get nlog3(n)<=T(n) So Theta(nlgn)<=T(n)<=Theta(nlgn) it is suffice to say T(n)=Theta(nlgn)

Great explanation!

thank you

Super sir,it's clear

The best proof

Y 5 over 16 in ex 4

Sir u must make the remaining topics videos

Hi, why is the depth k and not k+1, for example like a input of n = 32 and we reach a point where we know n/2^k = T(1). so 32/2^5 = 1. However, arent we excluding level 0, meaning the depth should be k+1?. And if we are excluding it, why did you incldue it back again when calculating the total cost starting from level 0 all the way to k-1? Thank you

thank you for the great explanation :))

lifesaving tutorial!

This is very straight forward.

best explaination

Absolutely amazing never seen explanation like this

amazing video! really helped me understand recursion trees! thanks man

Best vdo on RUclips for this concept ❤

galat padha raha hai bhai,,,18 ki jagah 14 hoga line 2 se

Awesome Bro !

are u muslim?

so if the problem is T(n) = 2T(n/2) + O(n) and we guessed T(n) = O(n), we follow inductive step to find T(n)<=cn+O(n) so is the problem T(2n)<=2cn+O(n)_1+O(n)_2 the next is T(4n)<=2cn+O(n)_1+O(n)_2+O(n)_3 and so on , because there are extra O(n) steps every time and it could exceed O(n) so it becomes loose upper bound? and can we conclude from this that the real upper bond is larger than O(n)? thanks

Sir agar attandance ka issue na hota to me saare lecs yahin se leta 😅😂😂

Great tutor ❤❤❤❤❤🎉

Very well explained, sir 😀. Your explanation is much better than my university professor's.🙃

I haven't seen such informative educational videos on youtube... More than brilliant . fantastically delivered sir . hat's off ..

best video fr,it think there is no "hard" topics,there are just bad teachers.

Does any value for n works for the last 2 examples?

Great

Life saver! Thank you!

i have a doubt in the first example for Ic u have taken K. n but in the second example u have taken sum of all the terms and also u have taken GP of infinite terms Doubt 1: why did you take infinite terms Doubt 2: why didn't you take K.N for second example

Sir, you are the best. I watched your other video on the master method and now this video, and everything makes sense. You cover so many different examples that it’s enough to fill my understanding of how the problem works, and you explain each thing so well that and slow enough so I can understand. Thank you, I have an exam today and this really helps 🙏

when we are finding log 2 and log 3 value why are we taking base 2 not base 10 for both

Kash Urdu m bol leta

Thank you 🤲

i love u sm this made sm sense