Introduction to Big-O Notation with Examples | Time and Space Complexity Simplified | Geekific
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Students and developers alike struggle when it comes to space and time complexity. So, if you think that you do also, it is totally fine, because in this video we explain in detail what complexity or the Big-O notation is and how to calculate it. We also went a step further and compared different running time complexities using examples and discussed how these complexities affect the performance of a given application.
Timestamps:
00:00 Introduction
00:26 What is Complexity and How to Calculate it?
04:58 O(n) vs. O(1) vs. O(n²)
07:37 Space, Time and Performance
09:22 Adding Complexities
10:25 Logarithmic Time Complexity
14:49 Multiplying Complexities
15:14 Thanks for Watching!
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Пікірлер: 3
So if N is 8 does that make nlogn = 8*3? Making it 24????
@geekific
2 жыл бұрын
The calculations were done only for logn am not sure what u r referencing. If N = 8, then 2 to the power 3 is 8 and 3 is the number of iterations required to reach the result. If in some other problem these three iterations where repeated 8 times each then yes we will have this.
@jonasmaoh1371
2 жыл бұрын
@@geekific i see no i was just wondering if iwanted to calculate the running time of a merge sort of N=8, which would be nlogn all i was asking was if n was 8 according to this formula would that make the running time 24 because 8×log of 8, btw i am not even sure which base i assumed the base of 2, which would make it 24, so i was asking if in that case 24 would be the running time or if that was a mistake