Why Is Merge Sort O(n * log(n))? The Really Really Long Answer.
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- Опубліковано 18 лют 2019
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Question: Analyze the total work that Merge Sort performs as an exact function of n, the length of the input list.
My Old MergeSort Video: • Merge Sort - A Step By...
The Infinite Series 1 + 2 + 4 + 8 + ... : en.wikipedia.org/wiki/1_%2B_2...
Logarithm Rules: www.chilimath.com/lessons/adv...
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Table of Contents (If you watch this all, you will know why Merge Sort is upper bounded by O(n * log(n)))
Bro, you should be the one teaching me algorithms instead of my college professor, good job!
In my 4 years of doing a Computer Science degree I never had a lecturer explain it this well
The patience you had to go through every literal step, god damn, much appreciated (once again) man.
How COME a person can be this talented at teaching? Thank you a million times!
Also found your videos through Leetcode. As someone without a traditional CS background, you have a talent for explaining things in a very clear way. I imagine making these videos must be exhausting, but I do hope you continue. Even if that means one per month :)
This man can teach a 12 y/o
First time I ever saw ANYBODY even attempt to explain how we arrive at log n or n log n or all these math conclusions. And I mean even in texts supposedly written to help you understand algorithms. Most times the lecturers/writers just rush to the final result. Way to go brother!!
Hey man, just wanted to add a +1 to the supportive comments. I absolutely love how you do not jump over steps assuming people know what's happening. I have a brain that needs to know why every step is included even if some might find it common sense, so this is wonderful for me. I subscribed to you because I think you deserve it. :) Have a wonderful day!
i'm graduated from uni, but my data structures and algorithms professor sucked. this section of CS has been the bane of my existence for a long time now, and i've really appreciated this video. thanks so much. i needed a long explanation like this.
This is nitpicking but according to the ISO 31-11 standard, log base 2 denoted as lb(x) for binary logarithm, where as log base 10 is lg(x), but log(x) is not defined in the standard. Personally I hate it. Why wouldn't log(x) be log base 10 and lg(x) be the binary logarithm? This is madness. Great video by the way. This is the videos I go to by default now cause the quick and dirty pretty visuals from other channels just don't cut it for me.
For those getting stuck at [
Coming from a non-computer science major, real understanding sorting part was always a real pain. (Even with my experience in working as a sw developer).
I found this channel through your comment in LeetCode, and I'm so glad I was able to find your channel before my tech interview. THANK YOU SO MUCH. KEEP IT GOING
You have just converted a process of time complexity of O(n ^ 1000000) to O(log n) in this video with your awesome teaching talent. Really like the way you teach with immense patience and dedication.
This is the best analysis out there, you leave me in awe with your explanations time and again. Really waiting for new videos! This was the only one I had left by mistake, sad that there's no fresh content coming from you on youtube. Anyways, thanks a ton for all that you are providing to the community!
^ THIS is how to teach
You are literally only youtuber who gives deep intuition behind this concept, you are giving us feeling like we could invent this by own, much respecttttt
You are a legend in teaching. Pure and simple explanation with a very patient attitude. It's clear that you don't do the videos to be done, you really want to transfer your knowledge, and you do it the best. I'm happy that i find you. Keep up the good work brother!
literally the best explanation i've ever gotten. i finally get it. i go to a top university but i regret wasting my money when your videos teach me better than my professors