DSA in Python – House Robber | All 4 DP Approaches | Recursion to Optimal | LC Medium | Part 193

📘 Welcome to Part 193 of Code & Debug’s DSA in Python Course!

Continuing our Dynamic Programming series after mastering Frog Jump—we now solve the classic House Robber problem from LeetCode. This is an excellent problem that builds on 1D DP patterns, where we maximize the stolen money without robbing adjacent houses. We’ll implement all 4 approaches step-by-step, evolving from basic recursion to the most optimal space-optimized solution, reinforcing key DP concepts like optimal substructure and overlapping subproblems.

This minimization-to-maximization twist on previous problems makes it perfect for practicing DP state definitions and transitions, commonly seen in coding interviews!

👨🏫 What’s covered in this video:
✅ Approach 1: Brute Force Recursion – Exponential time complexity
✅ Approach 2: Memoization (Top-Down DP) – O(n) time, O(n) space
✅ Approach 3: Tabulation (Bottom-Up DP) – O(n) time, O(n) space
✅ Approach 4: Space-Optimized Tabulation – O(n) time, O(1) space
✅ Complete Python code walkthrough for each approach
✅ Dry run examples with house value calculations
✅ Complexity analysis and solution evolution
✅ Interview tips and variations (like House Robber II)

By the end of this session, you’ll confidently apply 1D DP to maximization problems and optimize solutions for space efficiency!

🔗 LeetCode Problem – House Robber:
https://leetcode.com/problems/house-robber/description/

🔗 Article for understanding code:
https://codeanddebug.in/blog/house-robber/

📄 Full Playlist Sheet (All Questions in Order):
https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing

🎓 Enroll in the FREE Python DSA Course:
https://codeanddebug.in/course/master-dsa-with-leetcode

🚀 Advance Python DSA for FAANG (Zero to Hero Course):
https://codeanddebug.in/course/zero-to-hero-python-dsa

Stay focused and keep coding with Code & Debug.
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