🚀 neetcode.io/ - A better way to prepare for Coding Interviews

Will never forget my first day on the job where a customer requested a feature to find the longest increasing sub-sequence. A totally valid way to test someones competency as a developer

@btKaranDhar

2 жыл бұрын

Your sarcasam is depressive and hence ironic

@kotb2000

2 жыл бұрын

It is important to understand the idea of subsequences, use memory efficiently and understand complexities of exponentially increasing subroutines. A good Programmer is not the one who solves it the first time seeing it. A good Programmer is the one who understands all the dimensions of the problem and Learn as much as he can about underlying intuitions. and remember when Tony Hoare first made Quick Sort He didn't say I am not going to face a situation where I sort a customer's Needs. His attitude as any computer scientist when making a helpful research or an idea was If I am able to think How to sort and even invent a sorting algorithm then I am going to be able to satisfy my Customer needs who were Future Generations that used Quick sort in every Customer related Situation . Good bye.

@francisconovoa6493

2 жыл бұрын

@@kotb2000 gg

@zweitekonto9654

2 жыл бұрын

Which interviewer hurt you bro

@VibeBlind

2 жыл бұрын

@@zweitekonto9654 All of them

Please keep that tone and speed of voice. It really helps to "understand" the solution. All of us are here to "understand" the solution not just for a solution. You will do great my dude.

@shubhamsinghrawat6928

2 жыл бұрын

This how you except a google engineer

@AnupBhatt

5 ай бұрын

You can change the playback speed on KZread to make it go faster or slower. In case you find a problem that some other youtuber has solved, that Neetcode hasnt solved yet, use that feature.

You sir. Are the savior. Your made it so simple - some times you make me guilty why I could not think of it. Keep them coming!

"I really doubt your interviewer is going to expect you to get this without a hint; if they do I'd just walk out of the room" Probably worked great up until the layoffs 😥

@MaxFung

3 ай бұрын

yep, now it feels like every other interview problem has been next level. still some easies out there though :(

Thanks, great explanation as usual, who needs cracking the coding interview when this exists!

That was so simple and an epic explanation of how you can start thinking about approaching this problem. Being a beginner at dp, your videos help me understand how to start approaching a problem :) Thankyou!

This explanation went down so smooth -your voice was very easy to follow and your diagrams weren't sloppy and not complex to understand -this might be the cleanest solution I have seen for this problem for beginners to study!

Thank you for letting us know when we should walk out of the room. And what difficulty to expect in the interview :)

Your explanation is so great. The tone, voice, and the way you say are so clear. Thank you so much

Thanks for such a great explanation, I searched for it so many places, but I didn't find anything more than the formula. This video should have more likes.

I got it crystal clear now. You explained it very well. Thanks a lot.

Thank you for the clear explanation! For those wondering why going backwards in dynamic programming, you can actually solve this in forward dynamic programming, start from the beginning, too.

thank you omgosh this really is the best explanation one can find for this question on youtube

DP always surprises me. What a good approach. Thank you

excellent! This taught be how to choose subarrays recursively, and then the problem is trivial. Thanks a bunch.

"I'd just walk outta the room" you solve your own problem Mr interviewer LOL

Easily the best channel for leetcode solutions. So easy to understand and code is always clean and concise. Hats off to you, Neetcode!

Superb Explanation.Anyone having doubt in leetcode can refer this channel.Excellent video bro.I was struggling for this problem you made it clear.Thank you.

this is brilliant, I wonder who can think of this solution for the first time during the interview

This was a great explanation! I struggled with this, but I'm happy to learn some new techniques!

Was unable to wrap my head around this one. Your explanation was so nice!!

The best explanation video I have watched so far!

The video made it very easy to understand. Thank you for making this video. Keep up the work. I’m looking forward to view yours next videos.

One of the best solutions ever. thank you.

Best explanation out there!! Thank you for your efforts.

this is amazing, thank you for your hard work

Man this is the best video so far on this problem ✊🏻

Wow, what a great explanation! Thank you for the detailed step-by-step example.

Great explanation, as usual, thank you! :)

Awesome! Very clear and thorough explanation 🙂

Thank you very easy to understand and follow. I had problem understanding the solution on leetcode :)

You are great.. you explained it very well. Thank you so much!

This explaination is so so good. Thank you.

I came for that nlogn solution. But again, thanks for the tremendous help as usual

another day watching neetcode to help me with leetcode. Thank you!

Excellent oration of the logic and the ending is at another level.

This is GOLD!

You are awesome. Please keep it coming.

Really very helpful, explained in a crystal clear manner👌👌

Clear explanation! I believe you are the rising star in solving leetcode problem.

@NeetCode

3 жыл бұрын

haha, thanks I appreciate the kind words

even if it's not the best solution, it's the best tutorial for LIS I've ever seen

finally a good explanation and solution for this, thanks!

Yeah, I agree that being expected to find the O(nlogn) solution is walkout tier. I came damn close to figuring it out: use an ordered set to keep track of the elements you've inserted so far so that you can easily find the greatest value that's smaller than or equal to your current one. From here, assuming nums[i] is not your maximum thus far, there are two ways, and figuring out either of them is easily upper Hard level: either you actually delete the value you've found (the fact that this works because it means you can just return the size of your set at the end is incredibly unintuitive), or you mess with the way you store everything in the set so that you can still retrieve the index of the value corresponding to your found value (which is awful to implement).

@SunsetofMana

Ай бұрын

Why would deleting the value you found work? If you have input array [2,3,1,5,6] you cannot delete the value found at 5 when you see the 1, because then you cannot use it for the actual longest subsequence of 2,3,5,6 Tbh the approach of using a heap to store the subsequence length cache is quite reasonable imo… it’s annoying to implement but quite straightforward as an obvious improvement. If you know how to solve heap problems, which are based on the premise that a heap is a priority queue, why not just apply that here when you are searching for the largest element?

That sarcasm at the end made me laugh like hell😂😂😂! I'm also walking out from this problem

Really helped me out to understand this question!

@NeetCode

3 жыл бұрын

Thanks, I'm glad it was helpful!

Thanks for the explanation @neetcode , code in java : class Solution { public int lengthOfLIS(int[] nums) { int dp[] = new int[nums.length]; Arrays.fill(dp, 1); for (int i = nums.length - 1; i >= 0; i--) { for (int j = i-1; j >=0; j--) { if (nums[i] > nums[j]) { dp[j] = Math.max(dp[j], 1 + dp[i]); } } } int maxLIS = 0; for (int i = 0; i maxLIS = Math.max(maxLIS, dp[i]); } return maxLIS; } }

last statement : 'walk out of the room' really made me laugh😂😂.. that's the attitude

Not sure why, but this one felt much easier than the prior 3-4 problems in the Neetcode Dynamic Programming learning path. Got it on my first try, and solved it exactly the way Neet did. Just goes to show the value of the Neetcode Roadmap, and how the patterns start to solidify in your mind over time.

@engineersoftware4327

7 ай бұрын

That's correct, I feel the same way

noticing the subproblem 'is there an increasing subsequence with length m' is O(n), and m is between 1 and n, we can use binary search and get overall complexity O(nlogn). But it is way neater with DP

Thank you sir best explanation able to do in other programming language easily and concept is clear

very nicely explained bro thanks a lot

Best explaination!

beautiful explanation!

Agreeing with everything except the walking out part :)

博主讲的真好！

you're dynamic programming videos are all so well explained and helpful

Thanks, an excellent explanation!

@NeetCode

2 жыл бұрын

Thanks!

Optimal Approach O(nlogn) bisect_left is a python function which gives the lower bound of the element in O(logn) time. bisect_left(array, element, start, end) class Solution: def lengthOfLIS(self, arr: List[int]) -> int: subs = [arr[0]] for i in range(1,len(arr)): if arr[i] > subs[-1]: subs.append(arr[i]) else: subs[bisect_left(subs, arr[i], 0, len(subs))] = arr[i] return len(subs)

@davidespinosa1910

2 жыл бұрын

So if arr = [1,3,4,2], then subs = [1,2,4] ? That's not a subsequence. And yet it works. The mystery deepens... :-)

@paulancajima

2 жыл бұрын

@@davidespinosa1910 Yeah, the problem asks for the longest increasing subsequence. So, this will still give you the correct length just not the subsequence itself

really good tutorial!

"I really doubt your interviewer is gonna expect you to get the O(n logn) solution without a hint. If they do, I would personally just walk out of the room." XDDDDD

@noorbasha8725

9 ай бұрын

This happen with me yesterday, he didnt given any hint, result is i failed the interview

Wow great explanation!

Great video

Really nice explanation. Your video saved me lot of time.

@NeetCode

3 жыл бұрын

Thanks!

Thank You so much

whether it should be if nums[i] < nums[j] or if nums[j] < nums[i]

"I would personally just walk out the room" LOL

Best explain ever!

Thanks man!

Man 8 lines of code is all it takes, grate solution

lol you kept typing LIST great explanation, thanks!

End was epic 😄.. "I'll probably walk out of interview"🙃

Neat Explanation

"I would personally just walk out the room" haha

🎵 this is two, and this is two, so it doesn't really matter, which one we do. 🎵 Music by Neetcode at 13:34

It’s looks easier after your explanation 👏🏻

@NeetCode

2 жыл бұрын

Glad it was helpful!

thank u so much

thanks man pt. 2

It is interesting that you calculated DP from right to left. I think it also works if you do from left to right.

@briankarcher8338

Жыл бұрын

Yes it works both directions.

@kevinkkirimii

Жыл бұрын

@@briankarcher8338 i thought so.

DFS: O(2^n) DP: O(n^2) Binary search: O(n logn)

Great demostration starting from brute force, work way up to memoization and then leads naturally to dp!!! So Nice and easy it becomes with your approach! 1 question though: Why work from end backwords? How did you get the instinct?Could you please share your thougghts?

@NeetCode

3 жыл бұрын

I'm used to working from the end backwards because it's similar to the recursive approach. But it's possible and maybe more intuitive to start at the beginning. Whatever makes sense for you is the best approach I think.

@eltonlobo8697

2 жыл бұрын

Example: [1,4,2,3], While computing longest common subsequence starting from index 0, the number at index 2, will be used. While computing longest common subsequence starting from index 1, the number at index 2 will be used. What i mean by "Will be used" is i am asking a question: What is the longest common subsequence starting from index 2. So if we had started computing longest common subsquence from backwards, then when we compute longest common subsquence for index 0 and 1, we already have the answer for longest common subsequence starting from index 2 stored.

great explanation!

@NeetCode

3 жыл бұрын

Thanks!

the absolute goat

Please cover follow-ups also. BTW great explanation.

it would be great to see the n log n approach

@eduardoignacioroblessosa6349

4 ай бұрын

was looking for this comment

IDK why but your voice in this video sounds really calming

Thanks!

@NeetCode

2 жыл бұрын

Thank you so much!

Great video, much appreciated. However, I didn't understand the logical jump at @10:40 that suggested we were "starting at 3". I would have preferred to see a solution that proceeded front-to-back, because it seemed to me that is what you were doing in the recursive solution.

Elegant , great explanation .The video made it very easy to understand. 💭 Why I am not think like this ?. Thank you

Ty

No need to complicate it further by doing reverse looping, from 0 to n works just fine with the same function of max(lis[i], 1+lis[j]) for i=0 to n, j=0 to i if nums[j]

"I would personally just walk out of the room" I'm dead

When i feel its so hard to learn DSA problem and crack FAANG like companies my mind tells me "neetcode" and after seeing the video explanation i become calm and motivated to proceed further.

since we have already assigned LIS with value 1 for the length of nums, in the first for loop, we can start from len(nums) - 2 instead of len(nums) -1.

11:34 I think using the name LIS[ ] is not a good choice, as you may think the final solution is LIS[0] this way. The strict definition of this lookup table, let's call it lookup[ ] is this: IF YOU TAKE THAT NUMBER nums[i] into the sequence, then what is the longest you can get. So lookup[i] IS IF YOU MUST INCLUDE nums[i] into that sequence. If you write LIS[i], it sounds like it is the max NO MATTER you include nums[i] or not, which is not the case. So that's why in the code that follows, the final result is not LIS[0], but max(LIS)

"Personally, I would walk out of the room" - Yeah, man!

Great explanation. Curious about nlogn solution now.

@NeetCode

3 жыл бұрын

Thanks!

Thanks for the solution and simple and easy to understand explanation. However I wanted to ask why you initialized the outer loop like that because the first iteration of the inner loop won't happen because we initialize i as 4 right?

Damnnnnnn this was the bestest explanation everrrrrrr…..even better than clement

Why do you not cover the best solution: dynamic programming with binary search? That's the one I'm looking for because you need it to solve later problems like the Russian Doll Envelopes.

@CostaKazistov

Жыл бұрын

AlgoExpert covers it