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even if i understood it, you made a fanstastic job. thanks my man

we cannot use it as a[i] & b[j] it is not an array

Best explanation I've seen on it though, thanks! Just wanted to point out though that there is an off-by-one error in the code. The for loops need to be up to <= word1.size() , not < word1.size(), and the final result should be retrieved from dp[word1.size()][word2.size()]. Try the test case "abc" / "xyz" for an example with edit distance 3. I noticed that the initial array sizing with +1's - but the algorithm coded there (incorrectly) does not use the last column/row.

Thanks a lot!!!

nice explanation

A very insightful video. Just had one question around repair. Once we find a corrupted log wouldn't the data be insconsistent even after the repair? I am coming from the place where I have to use repair for a DB recovery

bro can you bring something with golang

Great explanation

So concise and on point

Thanks man. Will be using variable names going forward :)

cool video with brilliant explanation.

Thankyou so much for the explanation!! I have my finals next week and this helped a lot.

Supposing I want to Design and implement a distributed system that monitors and optimizes resource utilization across multiple nodes in a network. What changes do I make?

good video explanation thanks

You, sir, are a LEGEND!

very welll explained....

thank you

thank you very much!! Bhaiya.

amazing explanation!!!

Thank you. At first, I feel difficult to understand the problem. Thanks to your video, it is clear and easy to implement.

Why would you want the minimum health at the end? I would want maximum health especially if you can carry health over to the next floor. TBH, wasn't really paying attention and you may have explained it but I don't get what you mean by "wasting health" since you aren't technically wasting anything since if the goal is only to reach (2,2) from (0,0) as long as you get to the location then the optimal solution is taking less steps. Since both solutions are equal, except one solution results in having more health at the end, it would be safe to assume that MORE health at the end is better rather than having the minimum. Having the maximum health means you will be prepared for the future, while having the minimum means you can only do the single task. So if the rule was to get there with the fewest steps, then health is irrelevant outside of being alive upon reaching the destination. If the rule was to get there before the princess's health reaches 0, say after every step she loses health and has a number of health points, the optimal solution would be to get as much health for the knight as possible and the princess has the minimum required to reach the goal. Given that the only rule is to reach the princess without dying then there are two solutions. If the question was what's the minimum health required by a knight to reach the princess then the optimal solution is still Down-Down-Right-Right as the minimum health require is 6, not 7. At the same time, my knight would be stronger by the time I reach the princess and your knight would be the weakest. My underdog knight could continue adventuring.

I have seen your projects those are super awesome. Please guide me how have you started learning so deeply and how can i achieve it.

Thank you. Really good stuff !!

Thank you for the video, It was highly insightful !!

Great video please make more videos on low level stuff

really liked your vscode theme, please share

What a great video! thanks for the clear explanation!

Great stuff! Thanks a lot! Please keep posting such videos with such clear explanation. 👌

Great video on a topic I was curious about. Thanks!

Zoom screen so it will be clear

Absolute pillar of the grpc community, thanks for this brother!

Great stuff, please make more videos like this!

Thanks sir. Please More system design and golang services

Thanks for sharing.

I love Jyotinder Singh!

Nicely explained

Your charisma on camera is magnetic.

very insightful! please bring more videos like this

for the worked example starting at 10:17, in my opinion the explanations only work if we try to convert word2 to word1.

Explicit explanation. I got confused using a different video; but this helped me understand. Thank you!!!!!!!!!!!!

This was a great explanation, mate!

I literally couldn't understand the UCSD course and your video helped me out big time. Recommending this to anyone who struggles tbh

Great explanation! Only question is, why did we have to create dummy list? Why couldn't we do it with existing list?

Its very great explanation, im very understand it now

but sir, this is not levenshtein algorithm. coz for substitution it adds 2

17:13 i could not understand how we can perform replace and insert ? min of the (Neighbouring elements +1 ) so it is either replae vs insert. But To convert "re" to "d" the way i see is replace 'r' by d and delete it. Or am i missing something?

Really great explanation!! Thank you

this is insightful, thanks!

Very nice explanation brother

Great video. I watched 2-3 other videos on this same problem, but I still struggled to understand the algorithm. Your explanation was clear and easier for me to understand. Well done.