L2. First negative in every window of size k | Fixed Size | Sliding Window Technique скачать в хорошем качестве

L2. First negative in every window of size k | Fixed Size | Sliding Window Technique

🔥 *First Negative Number in Every Window of Size K | Sliding Window Technique* CLASS NOTES LINK - https://drive.google.com/file/d/1KBuW... Timestamps for quick navigation 👇 00:00 Introduction 01:43 Problem Identification — Fixed Size Sliding Window Concept 02:13 Brute Force Approach Explained (O(N × K)) 06:05 Optimized Sliding Window Approach with Queue 07:16 Window Movement Logic (Add & Remove Elements) 10:27 Why Queue is Used to Track First Negative Number 11:52 Optimized Algorithm Dry Run 15:19 Pseudocode Explanation Step-by-Step 17:48 Time and Space Complexity Analysis 18:34 Code Implementation (Complete Solution) In this video, we solve the classic sliding window problem *“First Negative Number in Every Window of Size K”* step-by-step with an optimal approach. You will learn: ✅ Brute force vs optimized solution ✅ How to maintain elements inside a window efficiently ✅ Using queue/deque for O(N) complexity ✅ Sliding Window pattern for interviews This problem is very important for coding interviews and helps build strong intuition for fixed-size window problems. 📌 *Topics Covered* Sliding Window Basics Fixed Window Technique Queue / Deque Optimization Interview Tips & Edge Cases 💻 *Code Implementation:* Explained clearly during the video. 📢 *Join My Community* 👉 WhatsApp Channel: https://whatsapp.com/channel/0029VaAZ... 👉 LinkedIn:   / pratham-jaiswal-97721a238   🚀 If you found this helpful, don’t forget to: 👍 Like 💬 Comment your doubts 🔔 Subscribe for more DSA content #DSA #SlidingWindow #CodingInterview #LeetCode #DataStructures #Algorithms #TwoPointers #Programming