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This is what I was looking for!

Absolutely loved this video! Thanks a lot!

Hello, curious, how come the Vehicle had a method called parkInSpot(). Would that violate the Single Responsibility Principal from SOLID? Why is a vehicle class responsible for parking when it should be handled by something like a ParkingSpot class? Thanks for your insight!

Could you share some discount for your subscription?

For the TF question (binary search) you forgot to stipulate that the input only has false, then true (can’t do TFTF) Also, the vocal AI had a hiccup at the 9m mark lmao

Very helpful bro!

Unable to buy your course from India. It say "Merchant is non-compliant with RBI guidelines for recurring payments and e-mandate". And yes I have international payments on on my card

Do you guys ask input size constraints in interviews?

I like how math is last resort

This helped me solve Next Greater element without looking at your code, thanks!

one of the best videos on the topic i’ve seen, thank you

For 10^8 inputs ? O(n) ?

Leetcode has nothing to do with the real-world programming in 99% of cases.

Thanks for the update, Anna! It is great that you are sharing your experience so that others can have hope.

😂😂

Damn, man, your dependency hierarchy is all over the place here...

Why is there an AI voice over?

Couldn’t you also go from left to right? You could store the indexes in the stack and as soon as you add an element greater than the element at the top of the stack, you keep removing the top until it’s equal or greater to the new element, while updating their values (sorry for the bad explanation)

where do i check this stuff out again?

Best Platform

great video

Thank you so much sir for the wonderful video

This is by far the best (and most painful😂) video on dp. I need to lie down

thank u so much

I kindly request that you should make videos avoiding moving backgrounds, as they can be distracting while concentrating . By the way, great explanation!

The best video on the whole channel. Great intro to the DP problems

Really good explanation. I'll agree with everyone else and say that the background is extremely distracting, and it actually makes the bitrate of the whole video go down, making the quality poor whether I select 144p or 1080p. I also feel like you didn't explain the algorithm before going through the problem with the heights of people. You started going through the example, but I didn't know precisely what it was you were doing or why you were making the decisions that you were making. I think it would be nice to have a plain explanation of the problem and how the algorithm solves it before going through the problem step by step.

This is a common question so want to make a special note here: - In an online coding assessment, you can obviously use this technique. - In an in-person interview, you should always ask for the constraints up front , as they are a part of the problem definition. The difference between n=10 and n=10,000 can entirely changes the problem. And requirement gathering is a key part of an engineer's skill set. Also make sure you know how to use the patterns: th-cam.com/video/RYT08CaYq6A/w-d-xo.html

That's a very useful way of solving problems in OAs and CP challenges but in an interview, you cannot rely on this trick. A lot of the times, the interviewer will not mention a specific constraint and would ask you to come up with as many solutions as you can. Starting from the bruteforce to as optimal as it gets. Therefore it is more important to learn problem patterns, you should only come to the constraint part when you're confused between two approaches.

But in some cases due to this we overthink to optimise the time complexity. I think this fails and make us overthink specially in case of O(N) ARMOTISED complexity

Absolutely, i just don't remember how many times i have been asked binary search like finding indices of the numbers repeated in a sorted array 😂

Pretty dumb video. Wasted 5 minutes

Thank you for making this :) Keep it up

really great man thanks!!

incredible insight, thank you

This is the first thing you do in a problem. What if a problem is easy because of input size and you're optimizing nothing, that's just premature optimization. For example, if you have a dataset of 100 rows and you need to implement some algo which is naively N^2 but you spend useless time making it O(N) and more complex, in any case that's a bad idea. Leetcode says a problem is easy/med/hard and that just shifts your thinking.

Is any one tell me.. Learning dsa is useful for careee or not?

but there are no jobs what would i do after learning all this?

in an actual interview even the interviewer might not know the correct input size, and wrong assumptions/guesswork will give you a much more lenient (smaller) input size leading to a more suboptimal approach than the interviewer is expecting (e.g. quadratic instead of linear)

Thank you so much

Algo monster if one of the greatest purchases of all time the ROI is actually insane especially for someone like me who needs order to learn shit and can’t just learn randomly

Thank you for making this video. I bought AlgoMonster subscription three days back and now I won’t regret it.

कर्मण्येवधिकारस्ते मा फलेशु कदाचन:।

Struggling with LeetCode? Not anymore! 🚀 These 8 patterns and templates are game-changers for tackling even the toughest problems! 🤯 I wish I learned these earlier - it would have saved me HOURS of frustration. If you're aiming to ace your coding interviews, this video is a MUST-WATCH! 🧑‍💻✨ ⚡ Pro tip: Stick around till the end for an epic bonus! 💡 time stamp: 0:00 - Intro 0:49 - Two Pointers 2:29 - Sliding Window 4:20 - Binary Search 7:34 - BFS 10:08 - DFS 13:08 - Backtracking 16:58 - Priority Queue (Heap) 19:01 - Dynamic Programming

Thanks for making this.

- **Introduction:** - 8 important patterns for coding interviews split into two categories: - **Linear structures:** arrays, linked lists, strings. - **Nonlinear structures:** trees, graphs. - Focus on pre-built code templates for these patterns. - **Linear Data Structure Patterns:** 1. **Two Pointers:** - Reduces time complexity to linear time \(O(n)\). - Two methods: - Same direction: used for scanning data in a single pass (e.g., fast and slow pointers to detect cycles or find middle elements). - Opposite directions: used for finding pairs (e.g., sum of two numbers in a sorted array). 2. **Sliding Window:** - Refines two pointers to manage a window of elements dynamically. - Expands or contracts the window to meet specific conditions (e.g., longest substring without repeating characters). - Often combined with hashmaps. 3. **Binary Search:** - Efficiently finds target in logarithmic time \(O(\log n)\). - Extends to lists with monotonic conditions, not just sorted numbers. - Example: finding the minimum in a rotated sorted array. - **Nonlinear Data Structure Patterns:** 4. **Breadth-First Search (BFS):** - Explores nodes level by level. - Uses a queue to keep track of visited nodes (ideal for level order traversal). 5. **Depth-First Search (DFS):** - Dives deep into one path before exploring others. - Often uses recursion and is memory efficient for exploring all paths. - Example: counting islands in a grid. 6. **Backtracking:** - Extension of DFS, explores all possible solutions. - Builds the solution dynamically by making decisions and backtracking on invalid paths. - Example: letter combinations of a phone number. - **Heaps (Priority Queue):** 7. **Heaps:** - Used for questions related to top K, K smallest/largest. - **Min Heap:** smallest value at the root. - **Max Heap:** largest value at the root. - Max Heap is used to find K smallest values, and vice versa for K largest. - **Dynamic Programming (DP):** 8. **Dynamic Programming:** - Optimizes solutions by breaking problems into overlapping subproblems. - Two approaches: - **Top-down:** recursive with memoization to store results. - **Bottom-up:** solves smaller subproblems iteratively using a table. - Too complex for this video but covered in-depth on their website.

Awesome!

You don't "need" to backtrack unless you're doing DFS, if you do BFS you can also get the depth and you don't "need" to backtrack

Remember , as long as you keep learning and improving ! You are on the right track ⚡️

This is a much-needed and real video I came across today. Thanks a bunch!