Not to undermine William but there’s RUclips channel “Inside Code”, he explains lot of concepts pretty well. He has dynamic programming content as well. Also a Udemy course on dynamic programming
@11:54 : It should be "Afterwards loop through all the *nodes* (not edges) of the graph and add all the nodes with an incoming degree of 0" This is a brilliant series. You teach in concise and clear manner. I first studied graphs in 2003 at college but never understood it and had great fear in the mind for graph problems. I found a great teacher after 21 years and I understand it easily. Thank you very much.
Great video. Small suggestion - right at the end where you check if index is not equals to n it would be really nice if you also showed an example of what would happen with your code if there was a cycle in the graph.
For anyone wondering about this, if you imagine a 3 node cycle, A -> B -> C -> A. Notice that you will never add these nodes to the queue because their indegree will never be 0. This implies that index will also never be larger than n.
I work from home. Why do I even need this getting dressed algorithm again? What an incredible breakdown, thank you so much for simplifying this complex topic so much for complete beginners like me.
HI ! Really nice explanation but I was wondering about the complexity why is it O(E+V) ? Shouldn't be O(V) since we iteratre of the nodes twice to set the degrees, then the while loop iterates exactly V times ?
Nice video. Is there a reason not to use Kahn's algorithm instead of the DFS topological sort in an interview since this is easier to memorize and code?
Thanks a lot, William for all these golden videos. I recently came across Aho- corasick and finding it really difficult to umderstand it properly. So I am commenting on the latest vdo here...hoping u would see my comment. We would be really grateful if u could pull up a vdo on Aho-Corasick. Thanks in advance.
We have to loop through once to find the vertices which have indegree of zero and put it in queue. After that we just have to pop the element and decrement in-degree of its dependent nodes. When you are decrementing you can check if it is zero or not. If it is zero than you can put that node into queue. This way you dont need priority queue. Only using queue will work in O(N+E) I guess.
Will this approach also work for cyclic graphs? *When I say it will work, I mean it will let us determine whether the graph is cyclic or not, or if a DAG will provide valid ordering.
What is the time complexity of calculating indegree? O(V^2) or O(V + E)? V = no of vertices E = no of edges Since there are two for loops, ig it should be v^2
Even tho you say that the in-degree array has to be number of nodes the current index is connected to indegree[0] = 0 Actually in code it seems like you're populating the in-degree by adding the number of nodes connected to the current index indegree[0] = 3
I've been running into a problem with this algorithm when there is no node 0. In this case, the inDegrees array will always have the 0th index be 0, and since there is no "0" node to add any incoming dependencies it will incorrectly add it to the queue. This also ends up breaking the rest of the algorithm since the true size of the inDegrees array is 1 less than what we were expecting. For example if our vertices are [1,2,3,4] the inDegree array at initialization will be [0,0,0,0] and will only match up to vertex 3, since at iteration it will be expecting i to start at 0. Has anyone else come across this and how have you solved this?
Hey Cesar, when labelling the nodes of the graph you should always label the first node as node 0, the second node as node 1, the third node as node 2 and etc... This should ensure that you always have a node 0, does this resolve your problem?
This video is simply great. When I read it first, it took 3-4 hrs to fully understand the algorithm. The video has done the same in 14min.
Repeated the same feat, RUclips recommendation to the rescue. PS Thanks @WilliamFiset
@@Aldrin32f did the same and now I am here😁
I just now Solved Course Schedule II on leetcode using this algo
My favourite ordering is to Keep Sleeping.
William, really appreciate your effort in making this Video! Effort behind this Animation is awesome, explanation is awesome too!
Clean and concise explanation. Easy to comprehend and remember. Thank you!
Hey William, just wanted to say thank you. If it's possible could you make a series on DP like the one you're doing for graph theory.
That would surely be the best DP course on RUclips. I love how he explains
Not to undermine William but there’s RUclips channel “Inside Code”, he explains lot of concepts pretty well. He has dynamic programming content as well. Also a Udemy course on dynamic programming
The freecodecamp video from Alvin Zablan on DP is as good as it gets
@11:54 : It should be "Afterwards loop through all the *nodes* (not edges) of the graph and add all the nodes with an incoming degree of 0"
This is a brilliant series. You teach in concise and clear manner. I first studied graphs in 2003 at college but never understood it and had great fear in the mind for graph problems. I found a great teacher after 21 years and I understand it easily. Thank you very much.
Really takes an effort to make it sooooooooooooo
SIMPLE🙏🙏🙏🙏🙏🙌🙌🙌🙌🙌
The way you explained is simply superb!! especially the "getting ready for school" example..
TIL Superman didn't know topological sort
Your videos and your teaching style are amazing!!
Thank you for a very clear explanation. Implementation was easy once I grasped the concept you've laid out in this video.
What an example to start with. Thanks for not starting with gibberish numbers. This makes more sense than all the other videos
Лучший канал по алгоритмам! Thank you William!
Thanks! It is great to see how the algorithm works in practice.
amazing explanation and visualization of the algorithm! a video unlike no other
Was following a course and couldn't understand this concept there but this video was so simple and better explained
great explanation as always. please make a video on segment trees next! such a powerful yet simple data structure
Great video. Small suggestion - right at the end where you check if index is not equals to n it would be really nice if you also showed an example of what would happen with your code if there was a cycle in the graph.
For anyone wondering about this, if you imagine a 3 node cycle, A -> B -> C -> A. Notice that you will never add these nodes to the queue because their indegree will never be 0. This implies that index will also never be larger than n.
This video helped a lot since before I would constantly wake up in the morning and put on my school before my socks
just looking at the playlists you made motivates me
Thanks William for the visualization and Animation! I clearly understand the concept now!
I'm about to binge watch all your videos. Thanks for the awesome content!
Wow. I understood that. Great way of teaching. You’re amazing. Thank you, sir.
Wow great explanation in only 13 mins!
Thanks a lot for the explanation. You've got a great gift of explaining complicated thing easy (which IMO is the sign of a genius mind)
That was a great example(dressing up) at the start of video.
thank you so much William! this is extremely helpful for beginners!
Thank you so much, it is the most clear explanation I've found.
Animation you conduct has heart beat sound as background. I like it :)
I work from home. Why do I even need this getting dressed algorithm again?
What an incredible breakdown, thank you so much for simplifying this complex topic so much for complete beginners like me.
Keep it up William. May you reach million subs next year !
Great clarity - quality content.
Thank you so much, I really appreciate your video. Please continue...
Awesome content! Thank you for putting in so much effort. Appreciate it!
I hope all of my professors are teaching the same as you. I really need a data structure 1 on 1 teacher to teach me everything
this is 1 on 1 teaching i believe
10/10 beautifully explained!
Thank you Wiliam, I finally understand what Topological Sort is!
Easy and simple. Marvelous.
Very nice explanation. please make a video on articulation point and bridges
thanks for explaning this so clearly!!
amazing explanation!
This video is a gem, thanks! You have a new fan :)
Thanks this video helped me optimize my sort code for leetcode course scheduling
Thanks Mr. Fiset really awesome explanation
Nicely explained - thanks for this.
What tool have you used to draw and animate these graphs? Thanks
Good as always. So easy to understand.
Kahn : Implements Topological Sort.
Superman : Am i a joke to you ? Wears underwear after pants.
Underwear -> pants -> shirt -> hoodie -> socks -> shoes -> school
Nice animation and great explanation, thank you
Thank you for your video, great explanation!
This was awesome! Subscribed!
I recommend this.........to all the before_watching_read_comments_section people 🙌🙌🙌
HI ! Really nice explanation but I was wondering about the complexity
why is it O(E+V) ? Shouldn't be O(V) since we iteratre of the nodes twice to set the degrees, then the while loop iterates exactly V times ?
beautiful explanation .. keep up the good work.. subscribed as well
Nice video. Is there a reason not to use Kahn's algorithm instead of the DFS topological sort in an interview since this is easier to memorize and code?
Thanks a lot man! I really appreciate your work!
Very nice explanation. Thanks
최고의 영상
this is 100 times better than my algo professor
Awesome, keep it up!
FANTASTIC. The problem with DFS on topological sort is that the recursion is too expensive, BFS is faster in all other aspects
Alternatively, we can implement the DFS topological sort algo, using stack.
Thanks a lot, William for all these golden videos. I recently came across Aho- corasick and finding it really difficult to umderstand it properly. So I am commenting on the latest vdo here...hoping u would see my comment. We would be really grateful if u could pull up a vdo on Aho-Corasick. Thanks in advance.
Thanks, You explained it really perfectly
holy shit this was such a great explanation, tysm!!
Best explanation ever, thank you!
We have to loop through all vertices to find those who have in degree of zero. Can we optimize this using heap or priority queue?
We have to loop through once to find the vertices which have indegree of zero and put it in queue. After that we just have to pop the element and decrement in-degree of its dependent nodes. When you are decrementing you can check if it is zero or not. If it is zero than you can put that node into queue. This way you dont need priority queue. Only using queue will work in O(N+E) I guess.
Where did you find the intro music for your videos?
just realized you have a similar algorithm for the dfs approach as well? , But I really like this, feels intuitive
Nice video, how is this different from another video you have on top sort using dfs?
Thank you for this awesome video!
You're the best man
great video! Thanks man!
What drawing software to use？ The picture is very nice
Excellent content.!
Will this approach also work for cyclic graphs?
*When I say it will work, I mean it will let us determine whether the graph is cyclic or not, or if a DAG will provide valid ordering.
hi there, quick question, based on the code, how do we make sure that we are not adding vertices that we've already visited?
Great Video!
Beautiful
wonderful explanation, thanks man:)
What is the time complexity of calculating indegree? O(V^2) or O(V + E)?
V = no of vertices
E = no of edges
Since there are two for loops, ig it should be v^2
What is run time , O(V+E) ? can someone explain line by line using the pseudocode if possible
Amazing
Even tho you say that the in-degree array has to be number of nodes the current index is connected to indegree[0] = 0
Actually in code it seems like you're populating the in-degree by adding the number of nodes connected to the current index indegree[0] = 3
Can we get the ppt which is being used in the video?
very good video
amazing.
Awsm!
can u post videos on identifying kadane's algorithm for dynamic programming
Regarding the DAG, isn't the (3) also not he DAG as the same reason that (4) one has?
MAH MANNN
great vid
Best😭❤❤❤❤
Dude just increase ur volume .no other complains .👍
Respect++
muhteşem yaa
I've been running into a problem with this algorithm when there is no node 0. In this case, the inDegrees array will always have the 0th index be 0, and since there is no "0" node to add any incoming dependencies it will incorrectly add it to the queue. This also ends up breaking the rest of the algorithm since the true size of the inDegrees array is 1 less than what we were expecting. For example if our vertices are [1,2,3,4] the inDegree array at initialization will be [0,0,0,0] and will only match up to vertex 3, since at iteration it will be expecting i to start at 0. Has anyone else come across this and how have you solved this?
Hey Cesar, when labelling the nodes of the graph you should always label the first node as node 0, the second node as node 1, the third node as node 2 and etc... This should ensure that you always have a node 0, does this resolve your problem?
@@WilliamFiset-videos Thanks!
my Saviour
Socks, shirt, hoodie before underwear! Picture that :D