This is hands down the best explanation of heaps. You're a very talented person, thanks so much for your efforts. You did in 19 minutes what my professor is incapable of doing in 3 hours.
00:10 Heap data structure helps in quickly accessing the most important task 02:26 Storing a complete binary tree in an array is more efficient 04:30 Sift-up and sift-down operations maintain the heap property in a binary heap. 06:48 Operations in a heap 09:03 Updating and building heap in heapsort 11:16 Understanding the time complexity of heapifying. 13:34 Heapsort is a sorting algorithm using the heap data structure with a time complexity of O(nlogn) 17:05 Heapsort has O(nlogn) time complexity.
Great video. I appreciate the work you put in these videos and the fact that you explain the concept very well (it takes real understanding to be able to teach something like this, unlike many channels out there wasting the viewer's time going through some example step by step on a whiteboard). Had to review some old stuff from uni and I'm so glad I found your channel :)
I'm completing the course called "Algirithms and data structures". There is only text explanation of such things and I thought "it's too complicated", but after your video everything became clear. Thanks a lot!
You're welcome! Yes a lot of resources lack visualization, which is necessary for some people to understand, this is why I'm planning to make a full algorithms and data structures course in this style
Really do appreciate you letting a thought/point/concept breathe before moving on. It gives the listener some time to process without noise (i.e. the presenter talking) before moving along with the lesson 👍
13:28 I like that you present the math here. Props for that. The following is not a critique of any relevance but I can’t help pointing out that I found the following steps a bit funny: 1/2^{k-1} = 1^{k-1}/2^{k-1} = (1/2)^{k-1}. It’s maybe a bit convoluted and didn’t need so many steps. But no worries really.
I believe there's a minor mistake in the explination here 2:50. Shouldn't we be talking the floor of (i-1)/2 ? Since if we are for example at index 7 then only doing (7-2)/2 = 2.5. And there can't be a 2.5 index position in an array.
@@insidecode I saw that later on, just wanted to point out to you if you want to edit the video position with a note saying it should be the floor instead of just how it is.
10:21 It makes sense that for constructing the heap, sift up (I hope I’m correctly recalling which one is which) is better than sift down and that starting from the bottom is beneficial. Is this the best one can do? If so do you know of a good resource for the proof? I might try to figure it out in my own, but it’s at least nice to know whether I’m trying to prove or disprove it.
This is a minor point, but when you do the analysis of the build function and you take the derivative of the geometric series, you should keep in your notation that you’re evaluating at x=1/2. You’re abusing the letter x, but I get that space was already tight.
Isn't heapsort supposed to have O(1) space complexity? In your code you create a seperate array that holds the sorted data which would make it O(n). In the implementations that I saw they use the same heap array for sorting as well. Any help is welcome :)
Great tutorial! My only note is (pretty please) use a pop filter when you record your voice over. The plosives are kind of distracting :D. Thank you for putting this together though!
think you skipped get max. I guess you could store a max heap with the min heap but that is 0n space complexity, or you could sort thru the array but that is 0n time complexity. Any other ways?
@@insidecode thank you that makes sense. I was under assumption we could call get min and get max in the same heap, but I realize you wouldnt call "get max" on a min heap.
That's IN SHA ALLAH really made me happy, to see a Muslim man making these great videos with easy and visual explanations! 🔥 Kudos to you 💯 keep doing the hard work, you will reach 1M some day IN SHA ALLAH!
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This is hands down the best explanation of heaps. You're a very talented person, thanks so much for your efforts.
You did in 19 minutes what my professor is incapable of doing in 3 hours.
Totally agree
Animated example in algorithm. YES PLEASE.
This is the best explaination with showing the flow of the program. TY Inside Code
Watching the heapsort at 15:25 was so fun! This is a great video. With excellent explanations and visuals, Great Job!
Thanks a lot!
Best explanation, seriously, all the graphics were so helpful! Thank you so much!
This is definitively the best video on heaps! Thank you for your effort
00:10 Heap data structure helps in quickly accessing the most important task
02:26 Storing a complete binary tree in an array is more efficient
04:30 Sift-up and sift-down operations maintain the heap property in a binary heap.
06:48 Operations in a heap
09:03 Updating and building heap in heapsort
11:16 Understanding the time complexity of heapifying.
13:34 Heapsort is a sorting algorithm using the heap data structure with a time complexity of O(nlogn)
17:05 Heapsort has O(nlogn) time complexity.
Very straightforward video with clear graphics. Appreciate your work!
wow. that proof for heapify runtime is so beautiful. take my sub for that
This is by far the best explanation I've seen on this topic! Thank you so much!
Great video. I appreciate the work you put in these videos and the fact that you explain the concept very well (it takes real understanding to be able to teach something like this, unlike many channels out there wasting the viewer's time going through some example step by step on a whiteboard). Had to review some old stuff from uni and I'm so glad I found your channel :)
I'm completing the course called "Algirithms and data structures". There is only text explanation of such things and I thought "it's too complicated", but after your video everything became clear. Thanks a lot!
You're welcome! Yes a lot of resources lack visualization, which is necessary for some people to understand, this is why I'm planning to make a full algorithms and data structures course in this style
Incredible way of teaching. Little step by step, beautiful and organized illustrations. Thank you very much :D!
The animations are incredible! I'm amazed at the detail
Really do appreciate you letting a thought/point/concept breathe before moving on. It gives the listener some time to process without noise (i.e. the presenter talking) before moving along with the lesson 👍
13:35 for people like me who get confused: the sum it's equal to 1/(1-x) for every x < 1 (in our case we have x = 1/2)
The use of a power series at 13:20 to find the time complexity blew my mind. I never thought about how time complexities are actually proved.
Very nice summary and illustrations of heap!
13:28 I like that you present the math here. Props for that.
The following is not a critique of any relevance but I can’t help pointing out that I found the following steps a bit funny:
1/2^{k-1} = 1^{k-1}/2^{k-1}
= (1/2)^{k-1}.
It’s maybe a bit convoluted and didn’t need so many steps.
But no worries really.
very elegant way of explaining heaps straight to the point simple but efficient keep the great content up 🙌
This video is one of the best I've seen on the topic. Simply brilliant! Keep up the good work!
14:22 time complexity of each operation.
build=heapify=make an array as a binary heap.
I believe there's a minor mistake in the explination here 2:50. Shouldn't we be talking the floor of (i-1)/2 ? Since if we are for example at index 7 then only doing (7-2)/2 = 2.5. And there can't be a 2.5 index position in an array.
Yes, this is why in code at 4:24 I wrote parent = (i-1)//2, a//b in Python is equivalent to floor(a/b)
@@insidecode I saw that later on, just wanted to point out to you if you want to edit the video position with a note saying it should be the floor instead of just how it is.
That won't be the case in languages like Java, as for integer-integer operations, decimal is ignored. So, it will give us 2 only.
Awesome explanation!
Keep up the good work, continue improving and one day your channel will be huge!
Wish I had watched this video in college when it was in my syllabus. Better late than never, great explanation, better than others.
Never Ever Stop Making Videos, That's All I Got To Say, Period !
10:21 It makes sense that for constructing the heap, sift up (I hope I’m correctly recalling which one is which) is better than sift down and that starting from the bottom is beneficial.
Is this the best one can do? If so do you know of a good resource for the proof?
I might try to figure it out in my own, but it’s at least nice to know whether I’m trying to prove or disprove it.
step by step animation + explanation that's what make the DSA to understand very clearly. Thanks a lot.... subscribed😊 please make more videos..
By far the best video about Heap-sort algorithm. Thank you!
Commenting for algorithm. Nice work 🔥
Appreciate it!
Algorithm haha 😂
Agreed, really good work 👏
The animations are super helpful, great job and thank you for such a good explanation!
This is a minor point, but when you do the analysis of the build function and you take the derivative of the geometric series, you should keep in your notation that you’re evaluating at x=1/2. You’re abusing the letter x, but I get that space was already tight.
Great Heap Video and Great Visualizations, Thanks!
Used to love ur videos but now I love these even more becaz of ur last word Inshallah
Never knew about the heaps . Again thanks for increasing my knowledge 😍😍🥰✌️
You're welcome!
Kayn akhay. char7 nadi, sauvitini, hit had partie mabghatch dkhol liya lrassi bmara
Best video on this topic. period.
The best explanation of heaps! Thanks!
You're welcome!
Remarkable illustration! Thanks Pal
@ 3:00 i think parent will be at (i-2)/2 not (i-1)/2
i want to ask how did you do the graphic effects and all stuff in the video which tools did you use? thanks!
of all videos I've scoured on binary heap this is the best
Thanks!
why is finding the element O(n) isn't it like a binary search essentially?
Isn't heapsort supposed to have O(1) space complexity? In your code you create a seperate array that holds the sorted data which would make it O(n). In the implementations that I saw they use the same heap array for sorting as well. Any help is welcome :)
Somehow I didn't know about the // operator in Python until now. For anyone confused, it does the same thing as math.floor (a/b)
best video ever for heap thank you
you deserve millions of subscribers
Great tutorial! My only note is (pretty please) use a pop filter when you record your voice over. The plosives are kind of distracting :D. Thank you for putting this together though!
Great stuff! Best explanation ive seen so far
Very good stuff, thanks for the compiling this video.
beautiful explanation!
Couldn't you use binary search on the heap to get the index so updating element always cost O(log n), since the heap is always sorted?
No the heap is not always sorted
Best explanation ever! I'm gonna buy your udemy courses!
Thanks a lot!
Man, that's cool, clear and understandable! Thank you!
You're welcome!
think you skipped get max. I guess you could store a max heap with the min heap but that is 0n space complexity, or you could sort thru the array but that is 0n time complexity. Any other ways?
Usually to use a max heap we just use a min heap but by switching signs of keys when inserting
@@insidecode thank you that makes sense. I was under assumption we could call get min and get max in the same heap, but I realize you wouldnt call "get max" on a min heap.
Thank you so much, this is a brilliant explanation
wow, best video of heaps ever
Thanks, great explanation!
Thank you so much! your video is real GOLD
put in the priority queue if two elements have the same priority the first one enters should be the first.
What do you mean by first one? First one in terms of what?
This video is a treasure!
great explanation
Great explanation. 🥂
this is such a good explanation
Thank you!
18:43 that got me
Great visualization!
You're welcome!
best explanation
Fantastic content
inshallah is something else ❤
Thank you, it was the best
Great content! Thanks for sharing!
You're welcome!
great video, brother! MashA Allah
❤❤❤❤❤❤ wowww
Great video.
this video is amazing
Amazing video
i fw this heavy, good shit fn
Can we connect on LinkedIn? May I ask your name?
I'm not active on LinkedIn sorry
super hard working
bless your kind heart
thank u so much amazing explanation
You're welcomee
Sooo good, thanks
inshallah i will pass my exams
BIEN OUEJ SYP
Sorry, but using x as a constant just doesn't feel okay 13:20
mash allah. bareekallahu feek
That's IN SHA ALLAH really made me happy, to see a Muslim man making these great videos with easy and visual explanations! 🔥 Kudos to you 💯 keep doing the hard work, you will reach 1M some day IN SHA ALLAH!
Genius!!!
thankyou
Love from india👌
Thanks!
@@insidecode bro i got placed in last week. Your vedeos helped a lot.
@@ismail8973 Where did you get placed?
@@sweetjimmy American Express
Thanks!!!!
Amazing
İnşaallah 👍
🤞👍👌
who else skipped the math part 😆
Legend
Thankss
you're muslim, didnt see that coming brother
Now when will I use this in an actual job? Likely never
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