Dynamic Programming | Set 10 (0-1 Knapsack Problem)

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Информация о Dynamic Programming | Set 10 (0-1 Knapsack Problem) | GeeksforGeeks

Название	:	Dynamic Programming \| Set 10 (0-1 Knapsack Problem) \| GeeksforGeeks
Продолжительность	:	19.11
Дата публикации	:
Просмотров	:	277 rb

Implement hill climbing algorithm for knapsack - code please
Comment from : @engineer5851

What Is n in function?
Comment from : @vamsikrishnasai1682

worst explaination can only be find at gfg YT😓😓
Comment from : @shashankpandey374

The explanation for the recursive solution was good but I don't know what happened when it came to DPbrThe explanation for the DP part could be better
Comment from : @tanmaygoel2880

Good efforts, fail to follow Explanation could be improved
Comment from : @surendharrudra1974

One of the worst Explaination I ever heard
Comment from : @vishalpatil4983

How to include the list of weight of final result in python?
Comment from : @HuongLe-qo7xw

What if all the weights are higher than asked weight Should we consider memoization instead of a bottom-up approach?
Comment from : @hrishabhg

Thanks a lot
Comment from : @vinaykumar5508

with recursion it seems rather easy, thank you
Comment from : @fakhriddinmakhmadiyorov7269

Why weight array was not sorted ??We have to sort the weight array
Comment from : @meenumeena919

I think creating a basic visualization of the 2d array used in dynamic programming will help us understand this problem better
Comment from : @sahulrajhansa8363

One of the worst videos of geeks
Comment from : @rithickrajkumar3739

Dear geeksforgeeks if you had included an explanation using tabular method before implementing code this will go to next level
Comment from : @maheshvangala8472

Great job bro
Comment from : @rethink20s

first example solution is 240 not 220
Comment from : @guptagopal

The maximum possible value is 300 if you add a weight of 10 upto five times which will not going to break the constraint can anyone explain how this 220 value could be the answer but not 300?
Comment from : @surajpark

very bad explanation
Comment from : @AshishSharma-li1dq

very poor explanation
Comment from : @neeleshrajpoot1493

Why didn't you use the table to explain that?
Comment from : @soumalyasahoo2664

You are literally reading out whats in your site Cmon man , dont post just for watch time
Comment from : @mrblacksanta

good job
Comment from : @TravellingBeast123

By using tabulation explanation can be made better
Comment from : @somyamishra5538

Can you please not chew stuff while trying to explain? It seems you have a candy or something in your mouth :/
Comment from : @Cyberbot009

good job!!!
Comment from : @monikajha4239

Knapsack problem can be explained much more easily using the table
Comment from : @souravmandal7527

The explanation doesn't make any sense! Confusing
Comment from : @jubaerhossain

not well explained and presenter is eating during presentation which is very awkward
Comment from : @AshishGupta-rh3jf

forgiven 2:31
Comment from : @bhargavreddy7038

sir actually in recursion i got full clarity but when its comes to the dynamic programing i'm not able get how many times does the 'w' for loop(2 for loop is iterating) can you it ?
Comment from : @bhanuprakashchinthakayala8123

The way you have explained, unfortunately, shows that you are fed up with what you are doing
Comment from : @boldschool6308

Compared to the previous tutorials this one is really difficult to understand Especially the optimal problem Using k[][]
Comment from : @nitishdash

Not a good presentation seems to be novice who is rushing into solution could have taken a retake with something better good luck next time
Comment from : @YouTuber-lb9ot

Nice one
Comment from : @shubhambhattacharya6046

sry but I had to say this compared to the other videos this video was really confusing!
Comment from : @SUBRONEEL

the mic quality is bad I would have read from a script to ensure I do not stutter while speaking
Comment from : @TheGreatOne428

The space complexity for the recursive solution is not O(1) Considering the stack usage, the space complexity is the depth of the recursive tree, O(N)
Comment from : @SaishGersappa

dude you are not at all clearbrThe explanation is far more simpler than this videobrbrPS: Please turn off the fan
Comment from : @shubhamdhiman5198

How do i allow duplicates? say i want to add an item twice
Comment from : @tedsprogz

I mean this in the nicest way possible, but i cannot understand anything you are saying Your accent is too thick for me
Comment from : @tedsprogz

If you don't depict it with 2D array, its very hard for people to understand
Comment from : @sivar4300

nice one
Comment from : @sudhansupradhan6891

Poor explanation!
Comment from : @gauravsharma6414

Good videos one suggestionbrinstead of directly jumping on to the solution please provide the reason for the particular approach in a real life logic sense, as it would help understand why the solution is used, than just how the solution worksbrThese videos really help lot of people great service guyskeep up the good work
Comment from : @23loges1

explanation is very confusing
Comment from : @arnabkaycee

sorry to say this, but the explanation can be made better, comparing with the qulaity of presentation in the previous 6 videos in the same playlist which made dynamic programming look too simple :)
Comment from : @neelalexpaul

Hello please tell me on 6:29 why in second bracket when you didn't included n-th element it is n-1 I think it should be n-2 on second bracket - because you didn't include the last element
Comment from : @736939

I am referring your site for dynamic programming, its very helpfulbrPlease post more videos on Dynamic Programming (algorithm and its implementation in Java)brThank You :)
Comment from : @sandeshavhad7737