1 Heap Introduction and Identification

[@chetansahu1505]

This is one of your subscriber. I'm lucky to find your videos on youtube. Ive gone through every single video of yours that exist on youtube. Hands down content. Immensely satisfied. Nobody Nobody teaches better than you do. Could you please make more videos on topics like Trees-segment trees, Tries and graph. Please dont stop making videos. This world needs you and more like you(which I don't find anyone else other than you).

[@TheAdityaVerma]

Thanks a lot brother !! Really this mean a lot to me, Thanks. And yeah I haven't stopped making video, just kind of stuck as of now due to lockdown. Definitely will be uploading more content in near future !!

[@pankajkumarjha5-yriddcompu269]

@@TheAdityaVerma have completed your Videos on DP, Stack and going through heap.. please upload videos on Tree and Graph as well bhaiya... Immensely Immensely satisfied..

[@mohit7075-k9k]

@@TheAdityaVerma bhaiya plz graph and backtracking ka bhi bna do 🙏🙏

[@mayurigawande5973]

@@TheAdityaVerma plz upload make video on graph and tree the way u explain is awesome

[@MuhammadIrfan-cj1cq]

@@TheAdityaVerma kb kroge bhaiya v waiting.... intern bhi to lgwani h really love the u teach :)

[@Apurva-Sonavane]

The man, the icon, Aditya Verma. You taught me DP, I cleared Microsoft.

[@mantenapragnyabala1711]

Hi can you please tell from where to do graphs and trees

[@shwetajha6700]

You are someone who gives any of the average student that confidence that even they can understand this programming concept . You are a great teacher .

[@soumyajitbasu8068]

Bhai Sahab! I have been a subscriber of you channel from the time there was 1k Subs on this channel. You are one of the best teachers who clears concept in simplest format! Awesome!

[@nikhilmishra7572]

I am now your patron on Patreon. I never became a patron before. But looking at this content I think it is worth it.

[@TheAdityaVerma]

Glad you think so Nikhil ✌️❤️

[@rajatjoshi9385]

Never seen any tutor who put so much effort to make sure even small things are cleared by re-iterating multiple times. Thanks a ton for your content which is saving a lot of efforts scrolling over the internet or by wasting money on fraudsters. You should probably start as a full-time educator :)

[@aarishfaiz7880]

If someone is Thinking to go with this playlist I just wanted to say Don't think just go and learn its amazing

[@sushantmehta6604]

Loved the "koi chakkar wali baat nahi hai sab samajh aa jayega 2 min mein" I am an SDE-2 in a Product Based startup and one thing that I have run away from is DSA. HLD, LLD round I can clear very easily but I always refrained from studying DSA. The interviews that mostly focused on system design were easily cleared but DSA-focused interviews were problematic for me. This series has been so clear and informative. Thanks a lot, Aditya for this valuable content. FAANG soon

[@vaibhavnayak3416]

Bhai tum karloge crack maang easily. All the best.

[@mayankmohit3414]

Hi @sushant My case is exactly the opposite of yours. I always refrained from learning HLD, and LLD and one of the reasons is, that I never got any good resources for that. We have already got an awesome DSA playlist of Aditya, you can go through it. Please share some good resources to start HLD, and LLD if you have them. Thanks

[@vaibhavnayak3416]

@@mayankmohit3414Gaurav Sen yt for system design, for documentation oo design website.

[@pranav288]

Layoff soon XD

[@VsEdits59]

@@pranav288 eggh what

[@kishanmishra9802]

best tutorial for heap, best teacher on youtube ,waiting for other data structures also

[@himansuranjanmallick16]

The real mentor of all tire-3 guys.... 🙏

[@proprem2957]

# HI BOSS Boss I am also from your college (MACT). BOSS Aapki video dekh kr dil khush ho gaya

[@ashnakhera5733]

Best explanation of Heap.I always had hard time in understanding Heap but finally understood it. Please make more videos on Graphs and Strings.

[@animeshanand6286]

yaa man, we are waiting for your backtracking series and also Hashing. man you transforming lives over here . respect

[@jayshree7574]

so after the dp series, back to your channel, literallly very vey excited for this series!!!!!

[@anjalikumari2796]

your way of teaching is awesome..please make videos on backtracking and trie.Please continue making videos..earlier used to hate ds but because of your videos and lucid way of explanation I started enjoying it and able to solve lot of questions

[@soniamalik4929]

Aditya u r a very fantastic teacher.So lucky that I found your vedios..bhott achi explaination...SB smjh aya....plz keep making such vedios on other DSA topics as well.

[@siddhantagarwal3780]

Flipkart ka base=16 hai or CTC 24 hai , best programming content on youtube ,big fan Aditya bro .

[@premparmar8897]

Just watched this heap playlist, Its superb !! I really appreciate your work. Pen n Paper > PC

[@paragroy5359]

Nice explanation sir....thanks for the playlist...doing a really great job..

[@sriramkasu]

thank you for ypur videos they are better standard than paid courses

[@piyushsaxena6243]

Best approach to identify a heap problem. Thanks a lot

[@Ankit214]

plz plz send more and more viodes excellent ......one of the ever ds concept proud of u bade bhaiya

[@aishikbhattacharya7823]

Hi, I am a student from NIT-Durgapur and can't really express how helpful your DP videos have been. I am definitely sure the heap videos are gonna be great too. And as a subscriber I have one request..please maybe try uploading more videos on various Data Structures and Algorithms..

[@xsuritox1058]

Are bhai tumi o durgapur a , naki bari chole gacho.... DP'r video gulo shotti e darun chilo, gfg te onek gulo practice korlam, tomar ki khobor, Actually amio DGP te tai excited hoye gachilam😂😂😂 Sorry to be creepy af😁

[@039saranshvashisht8]

best explanation of heap in all the videos i have seen on this topic

[@himanshud2611]

Commiting myself to practice atleast 1 coding problem daily. Will be updating here! Kudos to your amazing efforts bhaiyaa

[@niharikasinha3390]

god level explaination of the time complexity! Have done heaps before but not with this clarity!! Please make a series on backtracking!

[@geekystuffs6209]

Bhai itni acchi explanation ko dislike kaise kr lete hai log bhai ?

[@sarthakbhatia7639]

Thanks a lot!Will complete this series today!

[@varungupta5021]

bhaiya 1 idea hai same heap (stl) ko use karne ka :- just reverse the sign i.e -1* (element) while inserting and while popping out again multiply it by -1 this way we can use same heap function(stl) for min and max heap correct me if I am wrong.. lekin bhaiya aik shanbd mai = "MAZA AA GAYA!" more such videos needed!

[@davidsharma4117]

bhai big fan ,great work...your videoes are cristal clear bro...thanku for these videos

[@ansariaasif9079]

I just only say , THANKS MERE BHAI ❤❤

[@AdityaVerma-vc2wq]

why we do vextor in min heap @19:08

[@payalbhattamisra6985]

I watched your first video.good explanation.every student will be understand it.

[@nitiansatya]

Excuse Me Sir Good Evening Sir Excuse me Sir Love from NIT Bhopal Sir😇

[@varunsen2802]

Implementation of heap in java Min Heap --> PriorityQueue pq = new PriorityQueue(); Max Heap --> PriorityQueue pq= new PriorityQueue(Collections.reverseOrder());

[@Abhisheksdt]

In other term Implementation of Heap in java Min heap --> PriorityQueue pq = new PriorityQueue(); Max heap --> PriorityQueue pq = new PriorityQueue((a,b)->b-a);

[@radium990]

🎉​@@Abhisheksdt

[@365xDev]

abhi start bhi nhi kra mene apla video me smj gya aap bohot mst padhte ho

[@mohitsomvanshi9364]

Bhaiya aap ki saari videos awesome he but aap ne kaha tha ki app graph and tree me se ekk topic suru karenge july 2021 se so please complete your promise we are waiting for graph and tree series. Thank you so much and lots of wishes for you.

[@fanushaneef3926]

Bhaiya pure DS ke playlist daalo na. Aap jabardast samjhaate ho..great

[@ShudhDesiComedyQueen]

17:48 implement karne me aisi ki taisi ho jayegi.. cant stop laughing. :D

[@jiteshkumar3112]

brother waiting for your backtracking series...

[@maniratnaprasad6007]

Yes bro

[@jonu.1504]

Your wish fulfilled after 3yrs. He started backtracking series few weeks back.

[@ATULKUMAR-ep8sw]

@@jonu.1504Exactlyyyy

[@rakshapadiyar]

Dheeraj rakhe, koi chakkar wali baat nahi hein, abhi samajh mein ayega 2 minute mein😅😂

[@Anashwar-p3w]

i madara uchiha hereby declared you the finest and strongest dsa teacher in whole youtube

[@Deepakkumar-pm2kt]

ok bro, starting this playlist after your comment. Was searching for a latest comment rest are yrs old.

[@vinayakbhat8495]

Thanks for the wonderful explanation bhai!

[@adityachoudhary1637]

correct me if im wrong but hum n times insertion perform kr rhe hain and heap ki insertion O(log n) time leti hai toh time complexity toh O(nlog n) yahan bhi hogyi jaise sorting mein thi, lekin agr hum kth smallest mein minheap banaye n size ka toh heap ka construct O(n) time lega then k-1 times pop krlein toh O(n+(k-1)log(k-1)) time mein solve hojayega. Is it correct ? Pls do tell edit: Sorry for the doubt i understood basically hum insert humesha log k size ke heap mein kr rhe hain toh hr operation ke liye max time log k lagega hence O(n log k) .Great concept indeeed 👏❤

[@vikrantprasad5435]

Please teach GRAPHS, I am having a hard time there

[@ROHIT-gv7xk]

yes bhaiya

[@aman-tl9gd]

what exatly are u finding hard in graphs ? I guess topological sort , mst are some tough topics ??

[@moviesflix7082]

@@aman-tl9gd would you tell me from where should i do Graph?

[@moviesflix7082]

would you tell me from where should i do Graph?

[@shikharsaxena7211]

bhai ki class bole to ek number!!!

[@Kuriocity]

This is really good for revisions!

[@mohit8299]

Great video boss

[@adityaagarwal2324]

Bhaiya, apne heap ko stack se samjhaya par heap is a tree-based data structure. Confused.......plz reply

[@shreya-rs1fr]

loved your paper & pen tricks.

[@iampj874]

Is this aproach enought to solve "Minimum adjacent steps to reach the Kth smallest number"??

[@49-farhaanali86]

This guy is such a gem>>>>>>

[@rohitgupta7740]

Thanks bro , please make a playlist on linked list and trees ..

[@TheAdityaVerma]

Will try !! Next is Binary Search tho !! I was asked a question in my flipkart interview regarding binary search so I though it would be better to get it done first.

[@toofangaming6380]

Hey buddy nice job, really nice explanation 🔥🔥

[@Forever-lx5td]

Wow excellent teaching😇

[@GauravKumar-xz9uk]

more valuable than a paid course

[@tharunvoora1399]

I am lucky to find your videos 🤩🤩

[@swagatochakraborty6043]

7:00 But in worst case when k == n; then the nlogk will become nlogn --> Then we can use sorting too right?

[@adityachoudhary1637]

Thanks for the videos ❤ youre doing great work keep it up . If possible also do a live stream so that we can interact better 😁

[@Raj10185]

Aditya Bhaiya OP hai :)

[@PuneethSrinivas]

if we do in c, for kth/k smallest we can do min heap. For kth/k largest we can do max heap only

[@MohitGupta-ri9hf]

Hey Aditya, Please answer this. What if we use min heap instead of max heap I think it will give complexity as Klog(N) since we need basically two need steps first is to heapify the array using heapify (shift down heapify) which will take O(N) time and later pop k no. of nodes which will take O(Klog(N)) time. Isn't Klog(N) is better than Nlog(K) because we are putting N in log which is a bigger number and log will make it smaller which overall decrease the value of my expression . I really liked your video.

[@VishalSharma-hq5ti]

No, let say if k ~ N then your algo will take ~ O(N logN) but aditya's algo will take ~ O(N)

[@vishvapatel3641]

@@VishalSharma-hq5ti That is correct. But if k

[@ayansrivastava722]

@@vishvapatel3641 and not to mention, the k usually IS

[@thewanderingrooh]

just to add we can also use quick select method in these type of problems that run on average O(n)

[@VadayKapeed9999]

by adding all elements to the heap, the complexity anyways became nlogn as one insertion in heap is logn. Im not sure how nlogn becomes nlogk.

[@shrishtysrivastava9282]

Best content 👍 Please make series on graph and hashing.

[@gauravmishra8782]

please make videos on trees .I have completed stack playlist binary search .

[@SahilSharma-ug8xk]

As k is always lesser than n. So O(k log(n)) should be preferred over O(n log(k)) . So if we use the std::priority_queue (min) for kth smallest element with the predefined array. So making priority_queue will be O(n). then we can pop the k top elements . so it can be O(k log(n)) . can someone clarify this ?

[@RaviSingh-qd5pz]

The time complexity when we use min priority queue will be O(n+klog(n)) as we also need to include the complexity to create a min heap of n elements intially. So, the complexity will be more like linear (O(n)) than logarithmic. Hence the second method is preferred.

[@SahilSharma-ug8xk]

@@RaviSingh-qd5pz hi , but O(nlogk) is more than linear . With k > 2

[@vishvapatel3641]

@@RaviSingh-qd5pz But then we need to create maxheap, and it also consume time for heapify. Thoughts?

[@evergreen7781]

Cool video... So clearly explained bro 😊

[@positive-happy-bright]

Amazing explaination

[@M.m554]

Plz upload more on trees🌳 graphs... 🙂

[@yogeshsingh753]

bhaiya graph par kuch videos banayiye

[@bhuvneshjangid9138]

Love you brother.Your video is very helpful Thank you

[@swiftiests2852]

Ye banda, medical walo ko bhi software engineer bna dega. I guarantee.

[@lifewithniharikaa]

You are too good to be true.

[@damercy]

At 13:37, you said that when the size of heap is greater than 'K', then we pop the top element and push the current element... But shouldn't it be something like we should pop the top element only if the current element is less than/ greater than (according to question) the top element? In this question, shouldn't we do something like this:- If (q.top()>arr[i]){ q.pop(); q.push(arr[i]); } I'm not sure, just asking. And again, thanks for this awesome content brother! Liking and sharing this channel. :)

[@tabrezahmed1000]

We dont push, we assume by the implementation of the heap that the insertion happens perfectly in sorted order. Because of this we can safely always say that the largest element is at the top

[@abhineetpandey6414]

Time complexity would be nk if a stack will be used for implementing min/maxHeap

[@Sona-hb8dm]

your channel will be viewed by everyone so ,its should be useful hoping u will reach out in English..

[@SandeepKumar-rt2cz]

Bro we need more video on different topics love from Haryana 😘

[@madmaxfury9773]

Do with PriorityQueue in java8, by storing elements in descending order

[@satwikjain6177]

Bhaiya sets, priority queue, quick select algorithm.. In par bhi videos banao please

[@ShreyaSingh-vr9qi]

Nice explaination bro, keep making videos on DS, Algo.

[@TheAdityaVerma]

Thanks ! Yeah work is at progress !! Please like the video to help it reach to more audience.

[@skmn07]

@@TheAdityaVerma very nice..when are the next set videos coming?

[@TheAdityaVerma]

@@skmn07 did you watch all of it bro?

[@TheAdityaVerma]

next is binary search and coming soon

[@skmn07]

@@TheAdityaVerma cool. Can you pls post tutorials on greedy problems and graph problems

[@vaibhavlal5152]

I think if we use build heap that will take 0(n) and the retrieval of k elements will take 0(logk) . So the complexity will come down to 0(n+logk) which is equal to 0(logn).

[@drowningpool8356]

no, when we create a heap using heapify it takes o(n) and when we remove k elements, each will take logn so the time complexity will be klogn. and what he is doing is not heapify, he is inserting elements one by one which will take nlogk time, even tho he is removing k+1th element, he is still inserting it before removing it. so idk which is better klogn or nlogk

[@ArpitKumar-yo6up]

Thank you aditya bhaiya

[@uvedkhan1]

Hi @Adiya Verma, I read kth largest/smallest can further be optimized to O(N) instead O(NlogN) using the partition, could you please share the partition solution too if possible?

[@devanshprakash8354]

I think for kth smallest we will use min heap and for kth largest questions: max heap in JAVA Bcoz in java it's implemented via priority queue and u told by stack in c++. Correct me if I am wrong

[@nottheradbrad184]

u r right man,the same mistake he did in dp series where he mixed up memoization with tabulation.

[@shivangiraj7974]

Please can you make vedios on trees or tell me where can I study tree data structure (except for geeks ) for interview preperation. It will be a great help

[@rohitjha971]

Please make vedeos on graph and trees

[@TheAdityaVerma]

Thank you, I will try !!

[@kherakshay7854]

Bhai hasing and map ka playlist banado please

[@tridevthakur5397]

plz bro keep on making such video😊

[@AbhishekKumar-eh6zy]

what's the basic difference between heap and priority_queue

[@ishwarshelke128]

waiting for backtracking series...btw love to watch ur vdos

[@anshulmangal2755]

Please upload videos on tree and graphs

[@mr.jyotiranjankalta8098]

Aj Bhai ka birthday hai daba ke wish karoo. Happy birthday bro..........................

[@jivanninawe3190]

Bhahiya tree banao na playlist😁😁

[@soumodeepmaity2810]

why do you stopped making video. can you please continue making more video playlist.

[@AvikNayak_]

wish he continued making these videos. No one can build your intuition like him.

[@prabhatpandey1638]

If the Array is in decreasing order ie. [10,9,8,7,6,5,4,3,2,1] and K=3 , Then it will not work right as It will remove 10,9,8 in 3 iterations and on the last iteration it will return Top element which will be 7 but our answer is 3(as 3 is the 3rd smallest number). Can someone help me clear this doubt ?

[@payalbhattamisra6985]

Ans is 3 . k=3 means not to be 3 times iteration but iteration of every element present in the given array. max 3 elements present inside the heap.4 th element add hone ke bad top me Max value hoga wo pop ho jayega . I think it must be helpful to you .

[@prabhatpandey1638]

@@payalbhattamisra6985 Yes I figured it out later. Thanks

[@payalbhattamisra6985]

@prabhat pandey most welcome 😊

[@neerajmahapatra5239]

Inspiration😁

[@priyanshigupta1359]

awesome video bro

[@jayshree7574]

u r right, base 32 but ctc 14 hota h jo ni pata ksiko

[@danishsharma496]

Bhau heap , heap sort ,quick sort ye sab implementation DSA interview k liye kitna imp hia?