Hello Sir, Please write a book on Algorithms with the topic you covered . Your simple way of explaining complex topics is must have reference for a professional and student. I sat an entire semester trying to understand concepts like Big O , until now no one properly explained how log came inside Big O, no one talked about Frequency count method and taking degree of the polynomial. Keep up the good work and we expect a really good book from you. Just do the same what you wrote on the board to a book as it is instead of bringing in unnecessary Maths symbols like other university professors. When you explain each and every step unlike other lazy Maths teachers who skip steps, makes you a really good teacher.
Sir, u r really the best professor i ever encounter! I think u should have more courses on Udemy! Hopefully on all areas of Computer Science! I think there is a serious lack of someone who is able to teach in a way that is simple to understand. Please be the one to fill in this gap and i believe the Computer Science community will be very happy :)
Your videos are absolutely of finest quality. I have not encountered a teacher that convey information in such a simple, yet thorough matter as you do.
Sir, I have tried to learn about Asymptotic notations for a long time now. But wasn't able to grasp the concept. Thanks to you, I can now understand these.❤️
Again an excellent video. At 5:08 onward, I think there is a place for n! on that scale ( well depending on what that scale is) n^k < 2^n < n! inf thus the n^k < 2^n < n!
tomorrow are my mids, don't understand a damn thing what my professor taught in class, and here I am learning everything in 20 minutes, salute........ Love from Pakistan
I purchased udemy course by paying 89$ and didn't understand. Of after explanation this genius man, all concepts are cleard and it's became easy to code too. Thanks a lot sir. You'll always be remember by me♥
thank u sir...for making it so simple...i have a huge confusion on this topic but after watching ur video on assymptotic notation...i understand the whole concept..ur way of explaining is very simple..
*Sorry sir your videos are so intresting that I always forget to hit on the like button.* Thank you sir for all these content. You are a blessing for me.
Sir, all lectures are of best quality. Thank you for your efforts and soon I am applying for First Job and I will update you soon my status because your videos really help a lot.
Today I finished this video. Well explained sir i tried graphing and I understood clearly but to understand more clealy when there is no theta bound I have to see how graph differs for different lower bounds with n factorial example. Hats off to you sir.
5:10 - but you can same the same thing for n^2 and 2^n. Because if you use any number below 3, n^2 will be greater than 2^n. So it all depends on the value of n...
thank you for the series. I am planning to go on with the series till the end because its that good. However, i do have a suggestion on how this series can become even better. It would have been great if you provided some problems to solve after you finish teaching a certain topic. and then also provide solution to those problems so that we could check if we got it right. Incase we don't get it right, we can correct ourselves by looking at how you solve it.
What I don't understand is why is everything converted to n on the right for upper bound and 1 to the left for lower bound (4:22). Is there a specific reason we do that? For example, what if for n! i did something like n!/2< n! < 10n! just like we did in (n^2)logn +n at 2:48?. Now I have n! on both sides so can I express n! as a tight bound? If not, why? By the way amazing content!!. very helpful and concise. Very easy to understand.
Your calm demeanour helps so much. The way you simplify everything and how do you always know the doubts that come to mind. I guess this is a sign of a great tutor. To know where the students might struggle and cover those things before they become a trouble. Hats off to you sir. I became your fan in the first few videos only. If only I knew about your videos earlier. But koi baat nahi sir "der aaye durust aaye". 🙂🙂 12th ke baad pehli baar wo wali excitement feel ho rahi hai. Main ruk nahi pa raha hun. Lekin saturate na ho jaun isiliye ruk ruk ke notes banate hue padh raha hun. Just like those beautiful old days. You made me remember how much I used to love mathematics. Thank you for existing sir. It's a blessing to know you. I have a doubt sir : For the functions "n!" and "log(n!)"; can I write the lower bound as "n" and "log(n)" respectively ?? I think this satisfies the inequality too.
sir thank you so much. You made my concepts so clear. Tomorrow I have an exam and you save me. May you have everything in your life you want. Bless you
In coding interviews, they expect you only to analyse the O() condition. The reason being they themselves do not know how to analyse the other two, secondly it is not always possible to come up with a theta. But the prior reason is the most prevalant. I am watching your videos instead of reading CLRS.
Wow sir These lectures are very simple and easy to understand I wish our teachers taught us in the same manner Thank you so much and I appreciate you for what you are doing These lectures helped me a lot
2:16 let's say n = 1, then how is the right-hand side satisfying the condition with the middle one? right-hand side becomes zero where as the middle becomes 1. it would be looks like 0
At 1:14 he is taking n^2 for theta which is a lower bound and in lower bound we cannot take n^2 we can only take n under root n and log n so why is he taking n^2 please explain n^2 is an upper bound
I think he is wrong. n^2 can also be considered for theta & omega too, we can say by looking at Definitions. This example can explain why we cannot use O, omega, theta for worst, best, average cases. Because, cases happen according to the input.
You can say that for every natural number k, you have n! = Omega(n^k) so Theta(n!) sits before Theta(n^n) and after all the Theta(n^k) for k all. Now Theta(n!) can be a reference Theta itself. But if you want an equivalence using powers then Striling's formula gives you that n! is Theta(sqrt(n)(n/e)^n) or Theta(n^(n+0.5)/exp(n)). Also, log(n!) is Theta(n log(n)). You can prove that once again using Stirling's formula.
In asymptotic notations 1, he said that n, log n, n^2, 2^n, n^k, n!, and n^n are part of the upper bound, and doing Omega or Theta of any of these aside from n is incorrect. But here, he does theta(n^2). Why is that?
Hello sir, I believe that you can say that lower bound on log(n!) is nlog(n) also, as such: log(n!) = log(1)+ log(2) + ... + log([n/2]) + ... + log(n) > log([n/2] )+ log([n/2]+1)+ ... + log(n) > (n/2)log([n/2] ) correct me if I'm wrong, but that means that there is a tight bound for log(n!). thank you for your lectures! you are an amazing teacher!
3:54 Can't we use n^0 (N raised to power 0) to make it theta? Like ~ n⁰ x n⁰ x n⁰ x n⁰ - - - - - ≤ n!≤ nⁿ ; I understand it will still get reduced to 1, but if we keep the left hand term in terms of n, won't this work? (n⁰ ≤ n!≤ nⁿ)
I owe this man my cs degree. Greatest teacher of the generation
Hello Sir, Please write a book on Algorithms with the topic you covered . Your simple way of explaining complex topics is must have reference for a professional and student. I sat an entire semester trying to understand concepts like Big O , until now no one properly explained how log came inside Big O, no one talked about Frequency count method and taking degree of the polynomial. Keep up the good work and we expect a really good book from you. Just do the same what you wrote on the board to a book as it is instead of bringing in unnecessary Maths symbols like other university professors. When you explain each and every step unlike other lazy Maths teachers who skip steps, makes you a really good teacher.
@@abdul_bari yeeeeah. I agree with the guy. You explained the topic in such a simple way.
may i do that, i'll post it
@@simonedisalvatore6832 yas please
I completely agree with you
Ye ssir
Sir, u r really the best professor i ever encounter! I think u should have more courses on Udemy! Hopefully on all areas of Computer Science! I think there is a serious lack of someone who is able to teach in a way that is simple to understand. Please be the one to fill in this gap and i believe the Computer Science community will be very happy :)
Post breakup and abdul is my guru now. You've done the world a great service sir, and I thank you with all I have for that.
Your videos are absolutely of finest quality. I have not encountered a teacher that convey information in such a simple, yet thorough matter as you do.
best explanation I have ever seen so far. little bit of correction log(1*1*1 up to n times will be 1 )
so lower bound should be zero
scratching my head "how to get into competitive programming" and I find your videos!
No dislike represents how good u teach us. Many many thanks from Bangladesh...
Bruh, this looks like a troll comment now
07:52 such a awesome yet simple example! this one real life example literally made me understand the topic perfectly! i cannot thank you enough sir!
Sir, I have tried to learn about Asymptotic notations for a long time now. But wasn't able to grasp the concept. Thanks to you, I can now understand these.❤️
You are wonderful, Professor Bari. You are helping me SO much. I wish I had you worked at my Uni!
I felt relaxed when he stops after saying something and looking at camera 😂😂
Need people like to smile while studying 😂🤓
Same here
@unknown in that way u can learn fast u dumb
@unknown bruhh, wtf are you even saying
😂😂😂
Now I don't regret for not listening to online classes!
Thank you sir:)
1:42 He can tell I'm impressed and he doesn't even know me
😁😁😁
Bro is so humble its so comforting
Again an excellent video. At 5:08 onward, I think there is a place for n! on that scale ( well depending on what that scale is) n^k < 2^n < n! inf thus the n^k < 2^n < n!
That's correct, I was confused when he said that we can't put factorial anywhere.
We can go even simpler. My Algorithms class just covered the fact that n! can be bounded to n^n. It can be shown that (n/2)^(n/2)
You're so much more efficient than my algorithms professor, thank you !
Sir , the way of your teaching is amazing, you explained complex concepts in an easy and interactive way. Thank you, so much Sir ✨
tomorrow are my mids, don't understand a damn thing what my professor taught in class, and here I am learning everything in 20 minutes, salute........ Love from Pakistan
I purchased udemy course by paying 89$ and didn't understand. Of after explanation this genius man, all concepts are cleard and it's became easy to code too. Thanks a lot sir. You'll always be remember by me♥
You just saved my grade in real variables. Please keep making more videos, you'll never know who you'll save
thank u sir...for making it so simple...i have a huge confusion on this topic but after watching ur video on assymptotic notation...i understand the whole concept..ur way of explaining is very simple..
*Sorry sir your videos are so intresting that I always forget to hit on the like button.* Thank you sir for all these content. You are a blessing for me.
Sir, all lectures are of best quality.
Thank you for your efforts and soon I am applying for First Job and I will update you soon my status because your videos really help a lot.
These videos helpful?
DId you get the job, Ganesh?
Did you get the job Ganesh! INDIA WANTS TO KNOW!!!
why we put log 1 as 1 instead of 0
@@vimalkumar281 it must've been a mistake that the teacher oversee
Sir, your videos on Algorithm Analysis are simply amazing. Thank you so much for making such a wonderful videos, which are very useful.
sir you are my favourite. YOU teach algorithms like cakewalk.
Asalaam alikum sir after a long time i find such video from which i understand asymptotic notation JazakAllah sir
I just increased the playback speed and your content was still understandable,that is sonething we don't see regularly keep up the good work sir
Sir your video made my asymptotic notation concept very strong....thank you
Sir also for n factorial we can take omega(n)
This is great sir. I am finally learning algorithms properly through your videos.
abdul bariji thank you so much. what a fantastic teacher you are. crisp and clear explanations.
i honestly felt like giving up in my cs degree, and then you showed up on my page. I hope you know you made me feel hopeful!
Today I finished this video. Well explained sir i tried graphing and I understood clearly but to understand more clealy when there is no theta bound I have to see how graph differs for different lower bounds with n factorial example. Hats off to you sir.
5:10 - but you can same the same thing for n^2 and 2^n. Because if you use any number below 3, n^2 will be greater than 2^n. So it all depends on the value of n...
Sir By watching this lectures
I just bow down to you
thank you for the series. I am planning to go on with the series till the end because its that good. However, i do have a suggestion on how this series can become even better.
It would have been great if you provided some problems to solve after you finish teaching a certain topic. and then also provide solution to those problems so that we could check if we got it right. Incase we don't get it right, we can correct ourselves by looking at how you solve it.
This is one of the great explanation on Asymptotic Notations. Thank you so much Sir.
frequency count method was not able to understand but your videos a lot help . you are awesome sir and this video too
Sir your way of teaching is very simple and good
Sir literally you save me , a big thank you from my side. 🙏🙏🙏🙏🙏🙏
Hello sir superb explanation .Way to go hope in future you make more videos hope your teaching will reach every corner of the world.
No words to say
this man da goat he carryin all of us through college
You're the best teacher! Thanks for this video it helped me a lot !!
Just creamy and smooth as we want... ❤ Absolute treasure
a lot of these things are coming as magic and enthralling me
Best video on youtube. Thank you so much for making this amazing video!
What I don't understand is why is everything converted to n on the right for upper bound and 1 to the left for lower bound (4:22). Is there a specific reason we do that? For example, what if for n! i did something like n!/2< n! < 10n! just like we did in (n^2)logn +n at 2:48?. Now I have n! on both sides so can I express n! as a tight bound? If not, why?
By the way amazing content!!. very helpful and concise. Very easy to understand.
Bro did u find ur answer?? If yes then what is the reason??
I think it is not in the "class" sir talked-about
Thanks a lot sir. I understood this concept very well. You are a good teacher.
Thanks sir...your videos really helped to clear the concept of time complexity and asymptomatic notation
Your calm demeanour helps so much. The way you simplify everything and how do you always know the doubts that come to mind. I guess this is a sign of a great tutor. To know where the students might struggle and cover those things before they become a trouble. Hats off to you sir. I became your fan in the first few videos only. If only I knew about your videos earlier. But koi baat nahi sir "der aaye durust aaye". 🙂🙂 12th ke baad pehli baar wo wali excitement feel ho rahi hai. Main ruk nahi pa raha hun. Lekin saturate na ho jaun isiliye ruk ruk ke notes banate hue padh raha hun. Just like those beautiful old days. You made me remember how much I used to love mathematics. Thank you for existing sir. It's a blessing to know you.
I have a doubt sir :
For the functions "n!" and "log(n!)"; can I write the lower bound as "n" and "log(n)" respectively ?? I think this satisfies the inequality too.
Lower bond is defined as 1 Only
It is like a standard
ultimate style of teaching sirji.a big thanks to you.
You are very good teacher sir. Thank u for this algorithms course. I request you to keep your courses free as this one.
Yup
Life saver! This was a great instruction on the topic!! Thank you!
sir thank you so much. You made my concepts so clear. Tomorrow I have an exam and you save me. May you have everything in your life you want. Bless you
In coding interviews, they expect you only to analyse the O() condition. The reason being they themselves do not know how to analyse the other two, secondly it is not always possible to come up with a theta. But the prior reason is the most prevalant. I am watching your videos instead of reading CLRS.
Thank you sir ....U are easy way to understand to us ....Like dis type of related videos will upload more sir
I just love your style of explaining 😍
Cristal clear concept
Thank you sir 🙏
Wow sir These lectures are very simple and easy to understand
I wish our teachers taught us in the same manner
Thank you so much and I appreciate you for what you are doing
These lectures helped me a lot
2:16 let's say n = 1, then how is the right-hand side satisfying the condition with the middle one? right-hand side becomes zero where as the middle becomes 1.
it would be looks like
0
Absolutely incredible, thank you so much
Thank you Sir. I can't believe you made it so easy to understand.
Very well explained, Thanyou so much from USA.
PS: My professor sucks , doesnt explain anything at all .
@unknown LOL
Thank you professor. These are some spectacular explanations.
Professor you saved my life.
Sir, do you have tutorials for any other course? I want to know because, the way you explain any topic is very clear.
Thank you very much. You are a genius. 👍👍🔝🔝👌👌🙏🙏
How amazing your explanations are!!!
the video is literally awesome ..... and the example of mobile phone.....
At 1:14 he is taking n^2 for theta which is a lower bound and in lower bound we cannot take n^2 we can only take n under root n and log n so why is he taking n^2 please explain n^2 is an upper bound
I think he is wrong. n^2 can also be considered for theta & omega too, we can say by looking at Definitions. This example can explain why we cannot use O, omega, theta for worst, best, average cases. Because, cases happen according to the input.
THANK YOU ABDUL SIR, YOU'VE SAVED MY LIFE
Great, clear and simple explanation. Big thanks.
Sir please make a course on Competitive Programming on udemy.
You can say that for every natural number k, you have n! = Omega(n^k) so Theta(n!) sits before Theta(n^n) and after all the Theta(n^k) for k all.
Now Theta(n!) can be a reference Theta itself. But if you want an equivalence using powers then Striling's formula gives you that n! is Theta(sqrt(n)(n/e)^n) or Theta(n^(n+0.5)/exp(n)).
Also, log(n!) is Theta(n log(n)). You can prove that once again using Stirling's formula.
❤ Very Helpful. Keep up the good word Sir.
Thank you so much sir....
I will invite you in my graduation ceremony
In asymptotic notations 1, he said that n, log n, n^2, 2^n, n^k, n!, and n^n are part of the upper bound, and doing Omega or Theta of any of these aside from n is incorrect. But here, he does theta(n^2). Why is that?
This man is so good. Wow!
hello superb teaching. u r helping many students that's really great without expecting anything. god bless u sir
Excellent progression and crystal clear content. Thanks!
sala
you are one of my best teacher
Hello sir,
I believe that you can say that lower bound on log(n!) is nlog(n) also, as such:
log(n!) = log(1)+ log(2) + ... + log([n/2]) + ... + log(n) > log([n/2] )+ log([n/2]+1)+ ... + log(n) > (n/2)log([n/2] )
correct me if I'm wrong, but that means that there is a tight bound for log(n!).
thank you for your lectures! you are an amazing teacher!
Dono taraf n ki value same rakhega na ek jagah n/2 and ek jagah n kese chalega?
Nhi to sabhi ke thita oh ban jayega 😅
You are right, that's the lower bound not the tight bound
The best ever explanation 👏
at 1:57, teacher the value of n^2 logn +n is greater than 10n^2 logn for n=1.
3:54 Can't we use n^0 (N raised to power 0) to make it theta? Like ~ n⁰ x n⁰ x n⁰ x n⁰ - - - - - ≤ n!≤ nⁿ ; I understand it will still get reduced to 1, but if we keep the left hand term in terms of n, won't this work? (n⁰ ≤ n!≤ nⁿ)
thank you so much❤❤, I was struggling to know the difference
Thank you sir for making me understand this,I faced difficulties here
Thank you, sir your explanation is very clear and on to point . I'am very excited to learn data structures from your Udemy course.
Excellent content as other videos. Thanks a lot sir.❤❤
Sir, in the examples why we are not taking omega(n) instead of omega(1) ?
sir continue your video , we are geeting problem in linear searching, stack as well as much more
Thank you I learn lots from your learnings❤
You are the best, you saved me. Thank you So much.
plz cover more topic sir.....we want to learn more from u"❤❤❤❤❤❤
sir i am jagruth friiend , we both listened to your classes now we are class toppers thank you for teaching us.
Thank you so much for uploading these, you teach very well!!!
are bahut OP sir ji. Maja hi aa gaya
Thank u for uploading this video ....this was very much helpful
very neatly explained 👌👌