Meeting Rooms II Explained | Heap (Priority Queue) Solution | Java | NeetCode 150

#🚀 In this video, we solve the popular Meeting Rooms II problem from NeetCode 150 using a Min Heap (Priority Queue) approach.

You'll learn:
✅ How to identify overlapping meetings
✅ Why a Min Heap is the best data structure for this problem
✅ Step-by-step dry run with examples
✅ Java implementation explained line by line
✅ Time & Space Complexity Analysis

Problem Statement

Given an array of meeting intervals, find the minimum number of conference rooms required so that all meetings can be scheduled without conflicts.

Topics Covered
Priority Queue (Min Heap)
Intervals
Greedy Algorithms
Sorting
Java DSA
Coding Interviews
Time Complexity

⏱️ O(n log n)

Space Complexity

📦 O(n)

🔥 This is one of the most frequently asked interview questions at:
Google, Amazon, Microsoft, Meta, Uber, Airbnb, LinkedIn, and many more.

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Видео Meeting Rooms II Explained | Heap (Priority Queue) Solution | Java | NeetCode 150 канала LetsDoSomeCoding