LeetCode 300. Longest Increasing Subsequence | Brute Force, Dynamic Programming & Binary Search 🚀
Welcome back to Hack Code! Today, we're diving deep into the Longest Increasing Subsequence (LIS) problem, a classic question for coding interviews. This problem is perfect for mastering Dynamic Programming and Binary Search concepts in Python! 🐍
🚀 What You’ll Learn:
🔍 Brute Force Recursion (Exponential): Learn the basics of recursion by solving all possible subsequences.
📈 Dynamic Programming (Bottom-Up): Simplify with tabulation and understand how the DP array grows.
🕑 Binary Search & Patience Sorting (O(N log N)): Optimize with binary search to find LIS in logarithmic time!
Each approach is broken down step-by-step so you can follow along and understand each concept fully! This video is ideal for anyone aiming to boost their interview prep, especially for companies that value efficient coding solutions.
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📌 Timestamps:
0:00 Welcome!
0:08 Problem Statement
4:08 About Blind75
4:36 Brute Force with Recursion
11:24 Recurion Stack Explanation
12:50 Dynamic Programming (Bottom-Up) Intution
13:17 DP Dry Run
22:00 DP Algorithm & Code Explanation
25:33 Binary Search Approach
26:03 BS Dry Run
30:54 BS Algorithm & Code Explanation
35:47 Outro
📄 LeetCode Blind 75 DSA Sheet: https://docs.google.com/spreadsheets/...
🎥 LeetCode Blind 75 Playlist: • 🚀 Placement Mastery Series: Ace Your Tech ...
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