Window Sliding Technique | Why? What? When? How? | Comparison, Code Identification of Questions

The video includes following details-
0:00-1:00 - Introduction
1:00-2:12 - Question with Brute Force Approach
2:12-6:52 - Concept with example
6:52-10:28 - Code
10:28-11:36 - Why is it Dynamic Programming
11:36-13:40 - How to Identify Questions
13:40-14:45 - Dynamic Length Window cases
14:45-15:17 - Two pointer technique
15:17-16:15 - Variations of questions
16:15-16:28 - Thank you!
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[@saiyashwanth1991]

it's a pattern when you need to find something in the contiguous sub-array.

[@matrixRule127]

Actually, I was asked the same problem in my Paypal interview, but it didn't go well for me. Glad to actually find this. Awesome explanation. Thank you! 😍

[@KeertiPurswani]

😊😊

[@ankitranjan88]

Your intution to clear the topic meaning is very effective...as i understand it in one go!

[@zmxncbv95]

Thank you so much for the wonderful explaination, now I got some basic idea of Window Sliding technique

[@TUSHARSHARMA-zr1fc]

You explain so good, with no wastage of time.... Love ur videos❤

[@sdef719]

The explanation why this approach falls under dynamic programming is great. Learned a new lesson. Thanks ma'am.

[@KeertiPurswani]

Thank you 😊😊

[@CSharpProdigy]

awesome video Keerti.. Nice explanation... I'm making this my classroom from henceforth.. in the second loop, it should be arr[I] instead of arr[k] Thanks..

[@pranjalsingh1287]

I subscribed to your channel after watching several videos on your channel. Your videos focus on core concepts of topic and not just the particular problem(which other youtubers do) due to which we get a good sense of where these concepts can applied. Keep posting such videos❤️

[@rohandevaki4349]

can you tell which videos are focusing on core concepts? even i have faced the same problem on other youtubers videos

[@osvaldocarrillo1361]

Awesome, thank you!

[@aryankhurana1847]

Awesome!

[@krrishiyer1016]

The video is very well explained and detailed. Great work.

[@suryakantchavan7061]

Thank you nice one

[@sprajwal-lq3zz]

great explanation thanks.

[@vigneshhendrix4447]

I always love this sliding window approach! Whenever I get a prob on maximum sum subarray or product subarray,I apply this technique with happiness!😂🔥

[@KeertiPurswani]

Yeah, once you know this, it becomes easy😇

[@lokeshwaraachari6781]

Nice explanation mam ....you explained it from the scratch itself ,this is the first video I am watching in this channel and am impressed and subscribed as well... keep doing on this topics

[@urrahman196]

One more error to be noted in the coding you wrote- it should have been : arr[ i ] - arr[i - k] instead of arr[ k ] - arr[i - k] .

[@ayanroy8757]

best video on window sliding

[@tombrady7390]

your channel is small ,but you can be appreciate the fact that you helped the community and impacted us positively thanks :)

[@snehitvaddi]

Great explanation yar!! I could literally visualize everything by your hand gestures itself!! 👏👏👏

[@KeertiPurswani]

Thank you so much 😇

[@sreekanthjanapati409]

Nice explanation

[@debaduttapanda7816]

really helpful

[@pranavsingh1081]

Very good explanation

[@jitendraraghuwanshi1365]

One of my favourite techniques for arrays ,btw a great video!

[@KeertiPurswani]

Thanks! 😊

[@ishaankulkarni49]

very helpful!

[@prasadm3614]

M super glad that this video is in English !

[@deeyasings]

Helpful

[@DevLife_in]

It was a great video Mam, I loved it. I don't even know about you in my past but i loved it.

[@KeertiPurswani]

Thanks Divyanshu 🙂

[@haripriyaveluchamy9449]

mam ur explanation is too good

[@ashutoshkumar4267]

Great explaination, Thanks

[@KeertiPurswani]

Thanks 😊

[@Shredder220]

Your way of teaching is way more good than those highly paid tutorials...waiting for your next video like this maam

[@KeertiPurswani]

Thank you 😇😇 Many videos coming up!!

[@AritraBhattacharyya91]

Hi Keerti, Thanks for your awesome videos. Can you please create a dynamic programming concepts videos on how to identify and approach problems, find substructures etc. (if you already haven't).

[@divakarr6743]

I like the way you had explained this video because I was able to understand this completely, I do not see the continuation video for dynamic window size, Are you planning to upload it?

[@rudraksh9635]

Oh gosh , this is much awaited !!! Thanx a lot ma'am .. want more such videos , two pointer approach ! Btw loved ur content ma'am , thank you ma'am

[@KeertiPurswani]

I have discussed little biy about the two pointer approach in the end. My next video will be on that completely 😊

[@rudraksh9635]

@@KeertiPurswani sure maam , would be looking forward for the same , just increase ur content frequency by bit maam , if possible ..

[@akshayar2383]

@@KeertiPurswani Hi ma'am, when can we expect the two pointer approach video?

[@harshitakanal7411]

I really love your way of teaching, keep going di! 😃

[@KeertiPurswani]

Thank you so much Harshita, means a lot to me ❤️

[@priyachauhan813]

Hi Keerthy, Thanks for the content. I tried this in Python lst_2 = [1,2,3,4,5,6,7,8,9,10] k=5 wind_sum=0 for i in range(k): wind_sum=wind_sum+lst_2[i] max_sum = wind_sum for j in range(k,len(lst_2)): next_wind_ele = lst_2[j] - lst_2[j-k] wind_sum+=next_wind_ele max_sum = max(wind_sum,max_sum) print(max_sum)

[@arukshasilvie]

Hello, your videos are awesome, can you please explain monotonic stack/queue questions too ?

[@vivekjaiswar6825]

I know it seems a little late but ur code is incorrect it should be currentSum += arr[i] - arr[i-k];

[@jatinmalhotra2117]

very good explanation ! 👍

[@KeertiPurswani]

Thank you 😇

[@rydham8252]

Very well explained topic 👍👍.

[@KeertiPurswani]

Thank you! ❤️😇

[@sonupunia]

Hey Keerti your videos are very detailed and still easy to understand. Just watched few of ur videos and they were awesome. My fav is BFS and DFS detailed video.Can u suggest some reading resources that will help. Thanks a lot :)

[@KeertiPurswani]

Thank you so much Sonu. Means a lot. I have generally read from gfg, cracking the coding Interview by Gayle Lakman and Karumanchi 😇

[@hiteshgupta219]

The sliding window technique is my favourite one. Great explanation though !!

[@KeertiPurswani]

Thank you!! 😇😇

[@pawanagrawal7653]

Mam ur videos are very good, i have understood the concept very nicely.. Plss make a video on which covers all the algorithms like greedy, divide and conquer etc..and also attached some questions based on them...it will be very grateful.

[@KeertiPurswani]

Definitely! Many videos coming up 😇

[@chiranshuadik9818]

found an error... maybe? in your second loop, you are just taking diff of a[k] and a[k-i].. you need to include the maxsum as well.. otherwise the max() comparison won't make sense.. thoughts?

[@tejaswi4650]

Hi di, could you able ot provide the link to solving a problem of variable window size?

[@VinodMuda]

Hi Keerti, Nice explanation, but I think it is missing an edge case, what if nums[] is less than k, lets say nums.length = 3, whereas k = 5, in that case it will give ArrayOutOfBound Exception. My version of code, though I learned this concept from you :) static int maxMovingAvg(int[] nums, int k) { int i = 0; int result = 0; if (nums == null || nums.length == 0) return result; if (nums.length == 1) return nums[0]; if (nums.length < k) k = nums.length; while (i < k) { result += nums[i]; i++; } int maxResult = result; while (i < nums.length) { result += nums[i]; result -= nums[i - k]; maxResult = Math.max(maxResult, result); i++; } return maxResult; } public static void main(String[] args) { //int[] nums = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}; //int[] nums = {1, 2, 3, 4}; //int[] nums = {1, 2, 3}; //int[] nums = {1, 2}; //int[] nums = {1}; //int[] nums = {}; int[] nums = null; int maxResult = maxMovingAvg(nums, 3); System.out.println(maxResult); }

[@abhishekhorton79]

One of the most underrated channel fr

[@KeertiPurswani]

Please do help in removing the underrated part and share the channel with your friends. It will mean a lot to me! 😇❤️

[@aadarsh8839]

Shouldn't it be a[I] - a[i-k] ?? How we gonna slide if k is constant with a[k]-a[i-k] . Great explanation though , thanks

[@FinanceMode14]

NIce

[@suyashmisra7406]

Dear Ma'am,Thanks a lot for these tutorials. They are really helpful. I have a request ,if you don't mind. I'd love it if you could share some guidance on "off campus" placements,regarding anything "extra" that one must keep in mind while applying off campus. Since I have no experience of it,any help will be appreciated. Thanks in advance!

[@KeertiPurswani]

Was planning this already after few videos 😊

[@suyashmisra7406]

@@KeertiPurswani Really appreciate it. Can't wait!

[@ranitdey7369]

Your way of explaining the concepts is fabulous. keep it up!

[@KeertiPurswani]

Thank you. Means a lot! 😇😇

[@pokiripkr]

I like the way u say hi and I like ur voice

[@abcdabcd8605]

There is a mistake in the code at line line 6, it should be, wind_sum += arr[i] -arr[i-k]; and not as wind_sum = arr[i] -arr[i-k];

[@rahuldantuluri]

HI Keerthi, Great job as always. Little curious at 9:41 shouldn't it be arr[i] instead of arr[k]?

[@kurmasaideep4072]

yes bro .. i was finding where the bug was thanks for the comment🙂🙂🙂

[@ermahesh2009]

any real use case?

[@himanshugupta7010]

correct me if i wrong , but ig there at the loop k to n : you forgot to mention that we include the next element(after k elements )and excluded the first element i.e sliding the window .. you just did arr[i-k]-arr[k] which ig is not correct ... apart from this the concept explanation is fab..

[@shrenikpatodi4854]

👍

[@vjkumk]

wondering why 2 for loops are needed when it can be done by 1 while loop as below. here is the python solution. arr=[1,2,4,3,2 1,5] maxsubarray=[] maxsum = 0 k =3 i=0 while (i < len(arr) -1 and ( i + k)

[@bhanuchirutha]

I didn't see the warning at 10:12 and thinking how this code works

[@ishankumarsethi8773]

Mam please explain more on two pointer approach in your next videos.

[@KeertiPurswani]

For sure! Going to make a video on this!

[@aravind8731]

Hello mam, you had mistake on 9.42 it's arr[ i ] is not an arr[ k ] when you teaching it was right but you wrote accidentally wrong.

[@aayush5474]

Your explanation reminds me of aditya verma :)

[@KeertiPurswani]

That's a compliment!! He has another level fan following 😊

[@venkatkuncham2332]

Try with a gud mic,ur channel will go upto 1lakh subscribers easily (hoping to reach 1m😁),I like the way you explain.

[@KeertiPurswani]

Thanks @Venkat!! 😇

[@AgAnushree]

There is a small error in the code you have written. In first line of second loop the code should be window_sum += arr[k] - arr[i-k]. You have written window_sum = arr[k] - arr[i-k]

[@marketcrorepati5729]

correct I also got confused

[@charansai1133]

yeah i too observed that

[@rakshithd4942]

0:00 to 0:02: Is that a way to say Hi using the sliding window approach? 😂

[@vishalmittalvishalmittal]

Time Complexity of Naive approach should be O(N-K)*K

[@silverbullet_6]

better than most of the trash on Yt

[@amolmohadikar6716]

code is wrong it should be wind_sum += arr[i] -arr[i-k];

[@LeadCode1]

Aapko react aati h kya?

[@shaikfahim1232]

Didi aap bhi Adithya Verma bhayya ki tarah yek concept ko pakdo aur Usko detail me samjhado Koi notice kia hai kya Adithya Verma bhayya ki channel ke subscribers tho another level pe increase ho rahe hain Aur subscribers chahte hon to aap ka bhi kaam nikal jaayega

[@theexposerprint7574]

this code seems incorrect to me.

[@KeertiPurswani]

Hi, how is that? Could you please share more?

[@theexposerprint7574]

@@KeertiPurswani it's fine. you explained it very well.

[@KeertiPurswani]

@@theexposerprint7574 thanks 🙂

[@theexposerprint7574]

@@KeertiPurswani going to watch all of your videos. will let you know if i find any issue.

[@KeertiPurswani]

@@theexposerprint7574 awesome 😇🙂

[@MsBlueshark]

This didn't turn out that well

[@santoshjaishi3]

Tumme bahut jyada adss lagaya he.

[@lokeshwaraachari6781]

Nice explanation mam ....you explained it from the scratch itself ,this is the first video I am watching in this channel and am impressed and subscribed as well... keep doing on this topics