Max Product Subarray LeetCode Challenge

✅ Day 47 of 100 Days LeetCode Challenge Problem: 🔹 #152 – Maximum Product Subarray 🔗 https://lnkd.in/gcKQWrHz Learning Journey: 🔹 Today’s problem focused on finding the maximum product of a contiguous subarray. 🔹 Unlike sum-based problems, negative numbers can flip the result, so I tracked both maximum and minimum products at each step. 🔹 Whenever a negative number appeared, I swapped the current max and min to maintain correctness. 🔹 This allowed me to dynamically update the best possible product while traversing the array once. Concepts Used: 🔹 Dynamic Programming 🔹 Kadane-like Optimization 🔹 Greedy State Tracking 🔹 Array Traversal Key Insight: 🔹 Keeping track of both maximum and minimum products is essential due to sign changes. 🔹 Negative numbers can turn the smallest product into the largest. 🔹 Maintaining rolling states leads to an efficient O(n) solution. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

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