Hello Coding Lover,
Just Learn this Amazing technique which is discussed in this tutorial and you will be able to solve more than 10 questions on leetcode.

In this video, I have explained two pointer technique which is the optimal way to solve problems related to arrays, strings and linked list in O(N) time.

There are a lot of coding interview problems which can be solved by using this technique in an optimized way.
https://youtu.be/2wVjt3yhGwg
🔴 DONT CLICK THIS: https://bit.ly/2G4cEuc
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Hello Coding Lover,
In this video, I have explained a general approach to solve climbing staircase problem which is based on fibonacci pattern.

how to identify the pattern and apply the same to solve such DP problems.

Here I have explained, four different ways to solve this problem.

Recursive Solution
Top-down with memoization
Bottom-up
Efficient solution
https://youtu.be/ftpbBbtyxdE

🔴 DONT CLICK THIS: https://bit.ly/2G4cEuc

#JAVAAID #staircase #leetcode #javaAidTutorials #programming #dataStructures #algorithms #coding #competitiveprogramming #google #java #codinginterview #problemsolving #kanahaiyaGupta #google #facebook #amazon #oracle #gs #walmart

Hello Coding Lover,

In this video tutorial, I have explained the beautiful problem-solving technique called 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 and its applications.

If you can visualize this 2D image in 3D then probably you would have heard of 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻.

𝑺𝒐𝒎𝒆 𝒕𝒊𝒎𝒆𝒔 𝒎𝒂𝒌𝒊𝒏𝒈 𝒂 𝒕𝒉𝒖𝒎𝒃𝒏𝒂𝒊𝒍 𝒘𝒊𝒍𝒍 𝒕𝒂𝒌𝒆 𝒎𝒐𝒓𝒆 𝒕𝒊𝒎𝒆 𝒕𝒉𝒂𝒏 𝒕𝒖𝒕𝒐𝒓𝒊𝒂𝒍 :)

𝗡𝗼𝘁𝗲: if you find it useful, please do not forget to like and share your feedback in comments.

https://youtu.be/Sf-LR7OI-Ww

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Have you ever thought of how 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 𝘄𝗼𝗿𝗸𝘀 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹𝗹𝘆?
if not, watch this video to know the 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹𝘀 𝗼𝗳 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻.

In this video, I have 𝗺𝗼𝗱𝗶𝗳𝗶𝗲𝗱 𝗮 𝗽𝗿𝗼𝗴𝗿𝗮𝗺 𝗶𝗻 𝘀𝘂𝗰𝗵 𝗮 𝘄𝗮𝘆 that it will 𝘁𝗲𝗮𝗰𝗵 𝘆𝗼𝘂 𝗮𝗯𝗼𝘂𝘁 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹 which will help you in 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗶𝗻𝗴 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀.

Here are the outlines for easy navigation:-
👉 Recursion Flow Chart
👉 Recursion Execution Flow
👉 Tree Visualization
👉 Memory Visualization
👉 Demo

𝗡𝗼𝘁𝗲: if you find it useful, please do not forget to like and share your feedback in comments.

https://lnkd.in/fnEEdKs

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Hey Coding Lover,

This is the next tutorial in our recursion series. So far, we have learnt how 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 𝘄𝗼𝗿𝗸𝘀 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹𝗹𝘆?

Now it is time to dig deeper and understand 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 𝘁𝘆𝗽𝗲𝘀 𝗮𝗻𝗱 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗶𝘁.

In this video, I have tried my best to explain the 𝗵𝗲𝗮𝗱 𝗮𝗻𝗱 𝘁𝗮𝗶𝗹 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗶𝘁, 𝘃𝗶𝗮 𝗮𝗻𝗶𝗺𝗮𝘁𝗶𝗼𝗻.
which will help you in 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗶𝗻𝗴 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀.
Here are the outlines for easy navigation:-

👉 [𝟬𝟬:𝟰𝟭] 𝗛𝗲𝗮𝗱 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻
👉 [𝟬𝟲:𝟭𝟰] 𝗧𝗮𝗶𝗹 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻
👉 [𝟭𝟭:𝟮𝟯] 𝗛𝗲𝗮𝗱 𝗩𝗦 𝗧𝗮𝗶𝗹 𝗥𝗲𝗰𝘂𝗿𝘀𝗶𝗼𝗻
👉 [𝟭𝟱:𝟬𝟮] 𝗗𝗲𝗺𝗼
👉 [𝟭𝟴:𝟬𝟲] 𝗤𝘂𝗶𝗰𝗸 𝗤𝘂𝗶𝘇?

𝗡𝗼𝘁𝗲: if you find it useful, please do not forget to like and share your feedback in comments.
https://youtu.be/lG6HxO7cDRw
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Hi Coding Lover,

Here is one more tutorial which will 𝗲𝗻𝗵𝗮𝗻𝗰𝗲 𝘆𝗼𝘂𝗿 𝗱𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝘀𝗸𝗶𝗹𝗹𝘀.

Today, I have explained how to 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲 𝘆𝗼𝘂𝗿 𝗰𝗼𝗱𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗳𝗹𝗼𝘄 and get help from others if you stuck.

It supports most of the language like 𝗖, 𝗖++, 𝗝𝗮𝘃𝗮, 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁, 𝗧𝘆𝗽𝗲𝗦𝗰𝗿𝗶𝗽𝘁, 𝗥𝘂𝗯𝘆 etc.

𝗡𝗼𝘁𝗲: if you find it useful, please do not forget to like and share your feedback in comments.

https://youtu.be/TRMKJucB3B8

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Hi Coding Lover,

In this tutorial, I have covered the most common dynamic programming interview question 𝗟𝗼𝗻𝗴𝗲𝘀𝘁 𝗖𝗼𝗺𝗺𝗼𝗻 𝗦𝘂𝗯𝘀𝘁𝗿𝗶𝗻𝗴 which is usually asked in product-based MNC's.

Here I have explained the 𝗳𝗼𝘂𝗿 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘄𝗮𝘆𝘀 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 and below are the outlines-

𝗧𝗮𝗯𝗹𝗲 𝗼𝗳 𝗖𝗼𝗻𝘁𝗲𝗻𝘁:
👉[00:15] Problem statement
👉[02:17] Longest common substring
👉[03:00] Algorithm
👉[06:54] Recurrence relation
👉[08:00] Recursive solution
👉[09:42] Recurrence tree
👉[11:52] Top-down approach with memoization
👉[13:30] Bottom-up approach/ DP solution
👉[19:20] Demo

𝗡𝗼𝘁𝗲: if you find it useful, please do not forget to like and share your feedback in comments.

https://lnkd.in/faC5uGu

#JAVAAID #lcs #longestcommonsubstring #leetcode #javaAidTutorials #programming #algorithms #coding #competitiveprogramming #google #java #problemsolving #kanahaiyaGupta

Hi Coding Lover,
In this tutorial, I have covered one more common dynamic programming interview question 𝗟𝗼𝗻𝗴𝗲𝘀𝘁 𝗖𝗼𝗺𝗺𝗼𝗻 𝗦𝘂𝗯𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲 which is also asked in a lot of product-based MNC's.

Here I have explained the 𝗳𝗼𝘂𝗿 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘄𝗮𝘆𝘀 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 and below are the outlines-

𝗧𝗮𝗯𝗹𝗲 𝗼𝗳 𝗖𝗼𝗻𝘁𝗲𝗻𝘁:
👉[00:10] Problem statement
👉[02:44] Longest common Subsequence
👉[03:39] Algorithm
👉[07:06] Recurrence relation
👉[09:35] Recursive solution
👉[09:42] Recurrence tree
👉[13:22] Top-down approach with memoization
👉[14:51] Bottom-up approach/ DP solution (using 2-D array)
👉[25:10] Bottom-up approach/ DP solution (using 1-D array)
👉[30:11] Demo

𝗡𝗼𝘁𝗲: if you find it useful, please do not forget to like and share your feedback in comments.

https://lnkd.in/fNveH-Y

#JAVAAID #lcs #longestcommonsubsequence #leetcode #javaAidTutorials #programming #algorithms #coding #competitiveprogramming #google #java #problemsolving #kanahaiyaGupta