Agreed! These are great. More "Algorithmic Mental Models" for dynamic programming, backtracking, etc. would be extremely helpful. Thanks for the video!
I've never before seen a CS video that approached CS like math (i.e., here are the concepts, here are some keywords to look out for so you know when to apply these concepts, here are a few examples). The world needs 1,000 more videos like this (DP, Linked Lists, Trees, Graphs, etc). Fantastic work!
I came across this video after struggling with sliding window problems in preparation for my upcoming Google interview, and just wanted to thank you for the super clear explanation. I'm feeling much more confident with these problems now. 👍
Who even has the audacity to dislike such a video?? The best and simplest explanation of sliding window concept i have ever come across. Thank you sir!
I knew about Sliding Window but never fully understood the pattern of questions to target or saw it visually represented so well and simply. You should definitely consider doing a playlist of these patterns, super intuitive.
You might be a professor or a normal student, but your explanation skills are exceptional. Add to that most of the videos explaining algorithms do not include such an amazing visualization for the data structures that we are working with. I hope one day you will have the free time to make a full algorithms and data structures for competitive programming course with such an amazing visualization. Hope you the best sir whereever you are.
This is the best video I've ever seen on this topic "sliding window"! It does not only solve one or two interview questions for me but also solves a group of problems. More than that, it teaches me how to spot this group of problems. Fantastic!!!
31:11 The reason you "add 1" isn't because the array is indexed at 0. It's because the start element gets subtracted and it needs to be added back. Thank you for making the video :)
Great explanation! I'm a visual learner and I can see myself imagining these sliding window animations when I face array problems like this in the future.
What an excellent, well paced, well explained video with explaining the theory but also showing it in examples THANK YOU! The more you research the more you come to understand that trying to solve all these problems individually with out knowing about techniques like these, is so painful lol
Thank you @Ryan Schachte for clarifying the sliding window technique and make it so simple just like that. I hope you upload a lot more vids like this bro !
Was struggling a lot with sliding window problems earlier, your explanation really simplified those problems. I really appreciate your effort. Thank you! Please post more videos.
This is fantastic! Please make more of these 'mental model' videos. There too many videos out there that jump straight to the solution without any discussion of how to approach and generalize a problem. We need more video's like this!
I have always been calculating the first windowSum in a separate loop before starting to "move" the window in a separate loop. I never knew you could do both within the same loop without using a nested loop. This is amazing!
After watching this one, I could solve even the hard LC problems within 15-20 mins. This is a gem of a video on this topic. Hope you make more of these on other topics, I will literally pay for it
dude I am only 2 minutes in and I've liked and subscribed! Between the visuals and your consice explanations, the sliding window technique (which I never thought I'd understand) makes SO MUCH SENSE! Thanks so much :)
Max subarray sum of k is also a dynamic programming problem. You reuse the previous max result and update it. So it is like dynamic programming with space complexity O(1).
Incredibly simple explanation. I felt like a baby being handed his lego building blocks. I absolutely learnt a hitherto abstract concept, i will never forget.
This is such an awesome video by abstracting the idea of sliding window to tackle a group of specific issues with similarities. Regarding the question of smallest subarray for a given target, I think we need to add the constraint that every element in the array is positive. Otherwise, the sum can be reduced even if we grow the size of the window without dropping the front one. 28:37
for python lovers on the first question cur = 0 _max = cur t = [4,2,1,7] for i in range(len(t)): cur = sum(t[i:i+3]) if cur > _max: _max = cur else: cur = cur print(_max)
I have struggled with this concept for a really long time, but not anymore :) Your explanations were absolutely beautiful and I'm excited to solve some sliding window problems now! Can you please create more Algorithmic Mental Model videos? We'd all be super grateful!
@@TheSimpleEngineer Like the ones in "Grokking the Coding Interview: Patterns for Coding Questions". You explained this to me so well. Would be dope if you did that for patterns from that list. i like your teaching style my friend. I would pay money if you had a course explaining those.
@@TheSimpleEngineer Hi, Ryan. Hope you can clear something up for me. The solution for smallestSubArray isn't O(n^2) because you aren't looping over the array in the while loop, correct? You're just looping until the condition is no longer true. Is that right, or am I totally off?
This video just came up in my recs as I'm interview prepping and I'm so mad this is your only video like it! I thought I hit a goldmine for interview prep for a sec LOL, but nonetheless this video is amazing. Thank you so much
Wow I was amused by your teaching it all went straight into the head. Somehow RUclips algorithm suggested this gem 💎 . The fact that this video was made 4 years ago great content bro 🎉 🥳.Would be great if you make some more 'mental model' videos thank you, stay in good health ❤
@Ryan : In case of smallestSubarray method, if targetSum is 9, it is failing, need to add another condition in it. private static int smallestSubarray(int targetSum, int[] input) { int currentWindowSum = 0; int minWindowSize = Integer.MAX_VALUE; int windowStart = 0; for (int windowEnd = 0; windowEnd < input.length; windowEnd++) { currentWindowSum += input[windowEnd]; while (currentWindowSum >= targetSum && windowEnd > windowStart ) { minWindowSize = Math.min(minWindowSize, windowEnd - windowStart + 1); currentWindowSum -= input[windowStart]; windowStart++; } } return minWindowSize; }
The best explanation of sliding window I've seen so far. However one of my test case fails, and I am unable to debug the situation. This happens with the target sum as 9 and input array being { 7, 2, 1, 4, 4, 2, 2, 10 }. I should get answer as 2, but it yields 1. The problem seems to be in the last iterartion
![Pointers in C / C++ [Full Course]](http://i.ytimg.com/vi/zuegQmMdy8M/mqdefault.jpg)
One of the best explanations of this concept. Please make some more "Algorithmic Mental Models" based videos.
dude u seriously need to make more of these. Ill pay for them.
Agreed! These are great. More "Algorithmic Mental Models" for dynamic programming, backtracking, etc. would be extremely helpful.
Thanks for the video!
it is not one of the best, it is the best
@@CEOofTheHood Yes. Please make more of these. Especially with your new freecodecamp traffic this would really take off.
Agreed
I've never before seen a CS video that approached CS like math (i.e., here are the concepts, here are some keywords to look out for so you know when to apply these concepts, here are a few examples). The world needs 1,000 more videos like this (DP, Linked Lists, Trees, Graphs, etc). Fantastic work!
Dude please create a playlist for the other techniques as well!!! This is gold!
Does he have a playlist for this?
I came across this video after struggling with sliding window problems in preparation for my upcoming Google interview, and just wanted to thank you for the super clear explanation. I'm feeling much more confident with these problems now. 👍
Did you get into google? How was the interview!?
Who even has the audacity to dislike such a video?? The best and simplest explanation of sliding window concept i have ever come across. Thank you sir!
will it work if array has negative elements. I think no.
This is really the best video (or any, really) explanation of the topic I have found. Really hope this would become more popular. Thank you!
I knew about Sliding Window but never fully understood the pattern of questions to target or saw it visually represented so well and simply. You should definitely consider doing a playlist of these patterns, super intuitive.
This is the only video which made me understand dynamic window sizing algorithm... Thank you so much 🥰
Only 219k views... no way. This is by far some of the best CS-related content on RUclips, hands down. Amazing!!
The best lecture on sliding window technique
Guys, seriously, just study this video! It will help tremendously!!!
Thanks for such helpful content
1. Liked 2. Subscribed 3. Notifications Turned On. Please keep posting, one of best the best explanations for sliding window problems. Thank You Ryan!
I struggled for longest substring problems and now here we are i solved it by my own after watching your video thanks buddy
I found "Algorithmic mental models" is a great concept for solving problems please bring more videos like this.
Hands down the best explanation of the Sliding Window technique. Please do more algorithmic mental model videos!
You might be a professor or a normal student, but your explanation skills are exceptional. Add to that most of the videos explaining algorithms do not include such an amazing visualization for the data structures that we are working with. I hope one day you will have the free time to make a full algorithms and data structures for competitive programming course with such an amazing visualization. Hope you the best sir whereever you are.
This video gave the confidence that I'll mostly won't stuck in this topic anymore...Thank you : )
I've really struggled visualizing this algorithm concept and this video is extremely intuitive and detailed. Would love to have more of these videos.
I like that you actually name your variables in a meaningful way. 👍
Would love more of these 'Algorithmic Mental Models' videos. I'm sure everyone here would appreciate them.
@maryam I'm sure there are more capable people here who can help you. I don't have much experience with Python.
you are a very good teacher in layman language you are reaching. We will surely crack interviews with these
Learning from you to for my job hunt in Zurich, I shall get back to this video once I get my job ! Thanks in advance for everything!
The animation for second technique: dynamic SW is just awesome, I loved it
I am from India. THese are helping us cracking interview. THank you very much. Complicated topics you are making us understand very easily.
Nice explanation. I am glad I landed here while searching for all possible solutions for solving the array problems
This is the best video I've ever seen on this topic "sliding window"! It does not only solve one or two interview questions for me but also solves a group of problems. More than that, it teaches me how to spot this group of problems. Fantastic!!!
31:11 The reason you "add 1" isn't because the array is indexed at 0. It's because the start element gets subtracted and it needs to be added back.
Thank you for making the video :)
a simple visual explanation,
detailed, with variants
this is amazing, thank you
Thanks you with tear. You constructed a solid framework for handling sliding window in my head.
Great explanation! I'm a visual learner and I can see myself imagining these sliding window animations when I face array problems like this in the future.
This is probably hands down the best explanation of the Sliding Window technique i've seen. Great job!
agree 100%!
What an excellent, well paced, well explained video with explaining the theory but also showing it in examples
THANK YOU!
The more you research the more you come to understand that trying to solve all these problems individually with out knowing about techniques like these, is so painful lol
Wow great explanation, love the ‘teach a man to fish’ approach to the algorithm problems!
Thank you @Ryan Schachte for clarifying the sliding window technique and make it so simple just like that.
I hope you upload a lot more vids like this bro !
Was struggling a lot with sliding window problems earlier, your explanation really simplified those problems. I really appreciate your effort. Thank you! Please post more videos.
This is the best explanation on Sliding Window I have seen so far. Thank you for the detailed yet simple approach to explaining the concept.
This is fantastic! Please make more of these 'mental model' videos. There too many videos out there that jump straight to the solution without any discussion of how to approach and generalize a problem. We need more video's like this!
I have always been calculating the first windowSum in a separate loop before starting to "move" the window in a separate loop. I never knew you could do both within the same loop without using a nested loop. This is amazing!
why suddenly when i graduated all these channels poped up when i needed them the most , bro you are the best
After watching this one, I could solve even the hard LC problems within 15-20 mins. This is a gem of a video on this topic. Hope you make more of these on other topics, I will literally pay for it
I'm absolutelly blown away how this is explained.
One of the The best videos to explain Sliding windows concept. Request you to make other such videos that will help in tech interviews.
One of the best tutorials I have even seen. Thanks.
Fantastic, you should seriously consider doing dynamic programming series. Just 36 mins but got avery clear understanding of the topic
we need more of this series! please do more!
Thanks, I flew through LeetCode Sliding Window challenges after watching this.
Literally the best explanation of sliding window technique.
dude I am only 2 minutes in and I've liked and subscribed! Between the visuals and your consice explanations, the sliding window technique (which I never thought I'd understand) makes SO MUCH SENSE! Thanks so much :)
Please make more algorithm videos, you're literally the best explainer I have found on youtube.
Thank you for your help. Please add more videos to the algorithmic mental models series. please and thank you!
A series of algorithmic mental models would be awesome, great work!
I wouldn’t resist to pay a 1000$ to watch such videos. Brilliant piece of work! Hope you do more videos on “Mental models”
This video is amazing. hope you make more videos on "mental models" such as for dynamic programming.
Max subarray sum of k is also a dynamic programming problem. You reuse the previous max result and update it. So it is like dynamic programming with space complexity O(1).
One of the best and easy explanations of this concept. thank you so much !
Incredibly simple explanation. I felt like a baby being handed his lego building blocks. I absolutely learnt a hitherto abstract concept, i will never forget.
This is -by far- the best video on this topic I have seen. Thanks for taking the time to produce such a great content. Keep it up!
This is such an awesome video by abstracting the idea of sliding window to tackle a group of specific issues with similarities. Regarding the question of smallest subarray for a given target, I think we need to add the constraint that every element in the array is positive. Otherwise, the sum can be reduced even if we grow the size of the window without dropping the front one. 28:37
I love the idea of "Algorithmic Mental Models"! Thank you so much for explaining this perfectly and I'd love to see more videos for this idea!
wow this deserve to be a series very underrated!
I greatly appreciate the clear explanation of the dynamically resizable sliding window, it cleared up some doubts I have about the algorithm. Cheers!
Great guy. I was hesitant to watch the whole video but you were so informative that I actually learned something for many use cases. Thanks
for python lovers on the first question
cur = 0
_max = cur
t = [4,2,1,7]
for i in range(len(t)):
cur = sum(t[i:i+3])
if cur > _max:
_max = cur
else:
cur = cur
print(_max)
One of the best explanation on YT
I can't thank you enough. I wish I have seen this video before I bombed in the Meta interview. Please make more videos on Algorithmic Mental Models!!!
Rewatched some parts of it. Perfect, breathtaking. The best tutorial ever.
This is the best video for sliding window techniques
This video is pure gold!!! Great explanation . Everything is very clear. Thank you very much!
Great explanation, didn't know anything about sliding window before this video and I got enough information where I could implement it no problem.
I have struggled with this concept for a really long time, but not anymore :) Your explanations were absolutely beautiful and I'm excited to solve some sliding window problems now! Can you please create more Algorithmic Mental Model videos? We'd all be super grateful!
It's been three years since you dropped this video. I wish you would cover the other patterns.
What patterns are you interested in?
@@TheSimpleEngineer Like the ones in "Grokking the Coding Interview: Patterns for Coding Questions". You explained this to me so well. Would be dope if you did that for patterns from that list. i like your teaching style my friend. I would pay money if you had a course explaining those.
@@TheSimpleEngineer Hi, Ryan. Hope you can clear something up for me. The solution for smallestSubArray isn't O(n^2) because you aren't looping over the array in the while loop, correct? You're just looping until the condition is no longer true. Is that right, or am I totally off?
Only 13 minutes in but this is beautiful so far. Thank you.
I wish you made more of these videos. Thanks a lot.
This is the best explaination that i have came across 🙂
this is the best video I was watching about sliding window - thank you !!
This is the best video I have seen!!Please please please make more videos on Algorithm Models!!
Amazing explanation of the Sliding-Window Technique. Would love to see more of Algorithmic Mental Models.
Best explanation so far. Please make more videos on algorithmns
the best lecture available on any platform for SWT.
I loved this video and your way of explanation.
this was hands down the best explanation of this godforsaken concept i've been trying wrap my mind around for the longest.
This is amazing. I wish I could hug you for this best explainantion. I learned a lot.
for the max subarray problem you can also use the slice function between i and k and quit when k is greater than array length
Best explanation so far. Thank you
Please make more videos like this, it's one of the best things I've seen on youtube
This video just came up in my recs as I'm interview prepping and I'm so mad this is your only video like it! I thought I hit a goldmine for interview prep for a sec LOL, but nonetheless this video is amazing. Thank you so much
More to come ;)
solved many problems after watching this video. Thanks !!!
This is an awesome, thorough explanation of the sliding window concept and is easy to follow!
Best video for sliding window. Please make one for 2 pointers
Wow I was amused by your teaching it all went straight into the head. Somehow RUclips algorithm suggested this gem 💎 . The fact that this video was made 4 years ago great content bro 🎉 🥳.Would be great if you make some more 'mental model' videos thank you, stay in good health ❤
Nice video! Banger as a refresher for interviews.
The best sliding window technique I’ve come across thus far
Great explanation and example of sliding window.
@Ryan : In case of smallestSubarray method, if targetSum is 9, it is failing, need to add another condition in it.
private static int smallestSubarray(int targetSum, int[] input) {
int currentWindowSum = 0;
int minWindowSize = Integer.MAX_VALUE;
int windowStart = 0;
for (int windowEnd = 0; windowEnd < input.length; windowEnd++) {
currentWindowSum += input[windowEnd];
while (currentWindowSum >= targetSum && windowEnd > windowStart ) {
minWindowSize = Math.min(minWindowSize, windowEnd - windowStart + 1);
currentWindowSum -= input[windowStart];
windowStart++;
}
}
return minWindowSize;
}
This is a really great informative video, thanks for the hard work! I really like the breakdown to creating a mental model
Hand down, the best explanation. Great work🎉 thank you❤
Do you have a series for these Algorithmic Mental Models? Your video was extremely helpful and I would love to see more of these!
The best explanation of sliding window I've seen so far. However one of my test case fails, and I am unable to debug the situation. This happens with the target sum as 9 and input array being { 7, 2, 1, 4, 4, 2, 2, 10 }. I should get answer as 2, but it yields 1. The problem seems to be in the last iterartion
Great explanation and thanks a lot. The way you visualized really helped to understand the concept.
Explaind the Topic in an easy manner .Enjoyed the vedio and Found Really Helpful.
Please more videos like this, they are so good. Maybe some graph related videos?
I loved, looooved the format of this! Please continue to do these videos. Extremely helpful!!