Thank you for the amazing video and explanation. I had a question: I thought Big O accounts for all the operations taken, in this case every loop and every call to the function, instead of just the final function call with f(0).
Thank you! I have a series on both data structures and algorithms: ua-cam.com/play/PL7g1jYj15RUMeIY778b8lvgUzdRFnEniI.html ua-cam.com/play/PL7g1jYj15RUP_Mri9ym6BdUais6_jvhrS.html I do plan on making more videos on both data structures and algorithms in the future as well.
A small hint. Printing the string "***************" is only one operation. We aren't looping through the string and printing each character, we are just printing the string.
You only focus on the biggest of the 3 For example: 30! is much larger is comparison to 1 or 9, so much larger in fact it js negligible when we have to represent the time complexity
Explanation is very simple and clear. Easy to comprehend and you deserve more viewership.
Thank you for the positive feedback. I’m glad you think so 🙂
man you deserve more subscribers, thanks for simplifying, I have gone through so many videos and now i feel like i understand big O, thanks!
That’s awesome man! Sky’s the limit 🚀 keep it up!
One of the best and simplest video ever to understand Big O notation. Thank you for posting :)
I’m glad to hear that. That was the goal 🙂 thank you
This is the third or so video of yours I've watched. I liked it, saw you were at 999 subs, decided to be your 1k!
Grats man!
🤣😂 that’s awesome. I saw it sitting at 999 for a while 😅. Thank you very much for your support 🙏
Thank you so much! I think you should add the word "Recursion Explained" to make this video reach an even greater audience.
That's a good idea! Thank you 😃
I can't believe that i understood this in one vedio..
thanks bro
I’m glad! No problem 😉
11:19 😮 amazing
This is the best possible explanation I have ever seen. 👍
Thank you! I’m glad it helped 🙂
This is one of the best explanations for big O . thanks
🙏 thank you! I’m glad it helped
Best explanation I have seen so far on the time complexity. I subscribed your chennal after I watched your first video
That’s awesome 😎 thank you 🙏
Thanks for the simple explanation
Happy to help 🙂
You made it simple....Superb explanation✌
Thank you ! 🙏
good explanation thanks
Happy to help 🙂
Thank you for the amazing video and explanation. I had a question: I thought Big O accounts for all the operations taken, in this case every loop and every call to the function, instead of just the final function call with f(0).
Hey! I think you might benefit from watching the entire series. we only care about the dominant term ❤
@kantancoding Thank you, for your reply ❤️ I will be watching the entire series.
thanks it was very helpful
Thank you, glad I could help!
+1 Great video 😀
Thank you! Please don’t hesitate to check out the other videos in this series ❤️ I think you will find them helpful. Thank you for watching 😊
Thanks for the video and nice explanation. Do you have any plan to make data structures and algorithms videos?
Thank you! I have a series on both data structures and algorithms: ua-cam.com/play/PL7g1jYj15RUMeIY778b8lvgUzdRFnEniI.html
ua-cam.com/play/PL7g1jYj15RUP_Mri9ym6BdUais6_jvhrS.html
I do plan on making more videos on both data structures and algorithms in the future as well.
I wonder if there are any programs with this exact complexity
It seems for me the complexity is O(n * n! * s), where N is the number input and s is the length of * printed each time n == 0
A small hint. Printing the string "***************" is only one operation. We aren't looping through the string and printing each character, we are just printing the string.
You only focus on the biggest of the 3
For example:
30! is much larger is comparison to 1 or 9, so much larger in fact it js negligible when we have to represent the time complexity
try to make video in computer networking
😆 maybe some day but that's not necessarily my focus
@@kantancoding 😅 ok