LeetCode 198: House Robber | Python Solution | Dynamic Programming

📝 In this video, I solve the #houserobber problem where we need to determine the maximum amount of money that can be robbed without alerting the police by robbing adjacent houses. The optimal solution has O(n) time complexity and O(1) space complexity using #dynamicprogramming.

⏱️ **Timestamps**
00:00 - Understanding problem statement
00:59 - Brute Force Approach explained
02:26 - Big O Notation explained
02:59 - Using Dynamic Programming
04:13 - DP - Dry run
06:02 - DP - Big O Notation explained
06:45 - Python code walk-through
07:20 - Solution analysis - runtime + memory
07:28 - Conclusion

🔑 **Key Concepts**
• Dynamic Programming
• Bottom-up approach
• Space optimization
• Decision tree problems

💡 **Learning Points**
• How to identify when to use dynamic programming
• Optimizing space complexity in DP solutions
• Handling decision-based problems
• Converting recursive solutions to iterative ones

🔄 **Related LeetCode Problems**
• LeetCode 213: House Robber II
• LeetCode 337: House Robber III
• LeetCode 740: Delete and Earn
• LeetCode 1388: Pizza With 3n Slices

👥 **Target Audience**
This video is perfect for software engineers preparing for coding interviews, computer science students learning #dynamicprogramming, and anyone interested in improving their algorithmic problem-solving skills.

📚 **Prerequisites**
• Basic understanding of Python
• Familiarity with arrays and iteration
• Knowledge of recursive functions (helpful but not required)

🔗 **Links**
• Problem: https://leetcode.com/problems/house-robber/
• Solution Code: https://leetcode.com/problems/house-robber/solutions/6855377/dynamic-programming-solution-in-python-w-j3nb

📣 **Like this content?** Hit that subscribe button and ring the notification bell to never miss a new #leetcode solution! Drop your questions or alternative solutions in the comments below.

💼 **Additional Tips**
• Pay attention to the state transition equation: dp[i] = max(dp[i-1], dp[i-2] + nums[i])
• Notice how we can optimize space complexity from O(n) to O(1)
• This problem is a classic example of overlapping subproblems, making it perfect for dynamic programming

Видео LeetCode 198: House Robber | Python Solution | Dynamic Programming канала Code Scribbler