Welcome to my Big O Notations tutorial. Big O notations are used to measure how well a computer algorithm scales as the amount of data involved increases. It isn’t however always a measure of speed as you’ll see.
This is a rough overview of Big O and I hope to simplify it rather than get into all of the complexity. I’ll specifically cover the following O(1), O(N), O(N^2), O(log N) and O(N log N). Between the video and code below I hope everything is completely understandable.
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Code From the Video
Big O Notations
Thanks Derek. Great video as usual. I have a problem. Can you please help me ?
I need to extract text from 3rd-party applications. Something like when I chat on yahoo messenger, I need to extract the text and display it on my own application.
I know it’s outside of this tutorial but can you please help ? thank you thank you thank you 🙂
This isn’t something I have done, but this looks like something that can help you Microsofts UI Automation API. I hope that helps
Hi Derek, I don’t know anything about Microsoft UI Automation API and it’s not easy to learn. But thanks anyway. Have a nice day
Hi Derek,
Geat presentation. This video is really helpful however your a liitle bit fast but you teach very well. Maybe in your next presentation hoping you can do itlittle bit slower it ok with you, if not it’s fine too.
Anaway, I did try your code but I’m getting error with static time long variables. “Illegal modifier for parameter starTime and endTime. Do you have any idea?
Thanks,
Anthony
Thank you 🙂 I’m trying to make the videos as understandable as possible while also keeping them from getting boring. You may have noticed that I have recently slowed down a bit.
As per the error, there must be a typo some place. I noticed you typed starTime instead of startTime? You often see that error when you try to set visibility scopes (private, protected, etc) for local variables. I hope that helps
Hi Derek
Excellent video on BigO notations !!
Regards
Harsha
Thank you 🙂
Great video Derek
Thank you 🙂
Hi Derek,
Very good video and providing good ontroduction to Big O notation.
Thanks you very much for posting the video.
Thanks,
Venkat.
Thank you 🙂 I’m glad it helped
Hi Derek!
I just wanted to review important lessons from my Data Structure class and your video taught me a lot of new things I didn’t knew.
Great video, I hoped my Data Structure professor would give the right name for this topic when he introduced the class to measure how an algorithm scales.
Thank you 🙂 I’m glad I was able to add to your studies.
Hi Derek,
I have not gone back to school in 10 years! And I have been working in the tech industry for a while now…These videos of yours are just amazing and i wish my profs at school had taught with such enthusiasm. I have decided to study every day a little bit to keep myself in tune with the basics of Computer Science! Thanks and pls keep posting these!
Hi Matt,
Thank you for the nice compliment 🙂 It is very nice to hear that you are finding the videos useful. Many more are coming.
Derek
hi derek, may i ask about log(n!) as well as notations of exponential time. e.g. is 2^n+1 the same as 2^n
Regards
Hi Aaron, They are very close. It is exactly 2^n + 1. So they are just 1 different from each other
Hi Derek,
Big fan of your tutorials. One of my prof at college for design pattern course used to play your video in the class. Your video was more clear then prof’s lecture.
That is very cool! It amazes me that my videos are being played in colleges. Thank you so very much for telling me that 🙂
Hey Derek,
I am looking for a tutor. I was hoping I could find someone online. I understand your videos really well. Do you think you could help?
SCHOW
I provide a ton of tutorials and you are free to ask questions.
can you give me an example of BIG O notation?
Sorry, but I don’t understand the question