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Master the famous stock trading problem with at most K transactions! This LeetCode hard problem combines dynamic programming with clever state management to achieve optimal time complexity. Prerequisites: Basic Recursion Fundamentals: • Recursion in 10 Minutes: The 4 Step Secret... Mastering Recursive Leap of Faith: • Power Set Problem - Backtracking Simplifie... Understanding DP Fundamentals: • Memoization Simplified: Exploring Dynamic ... ⸻ Chapters: 00:00 Introduction - The K Transaction Problem 00:20 Problem Statement & Example 02:10 Finding the Subproblems 03:35 Buy-Sell Pairs Strategy 04:21 Define Function State 05:00 Initial Recursive Solution 07:01 Identifying Overlapping Subproblems 08:50 Can We Do Better? 09:22 The Key Insight - Optimized Solution Design 12:19 New Recursive Implementation 14:30 Updated Base Cases 15:30 Final Memoization 16:31 Time Complexity: O(NK) 17:02 Code Implementation 19:48 Next Steps! ⸻ What you'll master: The classic stock trading problem with K transactions Why greedy approaches fail for K more than 1 Building recursive solutions with multiple states State design for dynamic programming Complete implementation with memoization Practice More Problems: Visit https://trielab.io/problems to: Access complete solutions in C++, Java, Python Practice similar DP optimization problems Perfect for: Dynamic programming mastery FAANG interview preparation Understanding state optimization Connect with me: LinkedIn: linkedin.com/in/pijushcs Practice: trielab.io #LeetCode #DynamicProgramming #CodingInterview #LeetCodeHard #Algorithms #FAANG #InterviewPrep #Recursion #Memoization