Course Hive
Search

Welcome

Sign in or create your account

Continue with Google
or
DSA in Python - Subset Sum Equal to Target | Pick/Not-Pick DP | GFG Practice | Part 202 [Hindi]
Play lesson

Data Structures and Algorithms with Python | Free DSA with Python Course - DSA in Python - Subset Sum Equal to Target | Pick/Not-Pick DP | GFG Practice | Part 202 [Hindi]

5.0 (2)
23 learners

What you'll learn

This course includes

  • 73.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

Summary

Full Transcript

📘 Welcome to Part 202 of Code & Debug’s DSA in Python Course! In this video, we solve the classic decision DP problem: Subset Sum Equal to Target from GeeksforGeeks. Given an array and a target sum, determine whether any subset sums exactly to the target. We’ll cover the full roadmap from recursive intuition to the optimal space-optimized DP, mirroring our detailed write-up. This problem builds core DP thinking using the pick/not-pick paradigm and prepares for variations like Partition Equal Subset Sum and Target Sum. 🔗 GFG Problem – Subset Sum: https://www.geeksforgeeks.org/problems/subset-sum-problem-1611555638/1 🔗 In-Depth Article with Codes & Explanations: https://codeanddebug.in/blog/subset-sum-problem/ 📄 FULL Playlist Sheet (Every Video Listed): https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing 🎓 Enroll Free: Master 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. Like | Share | Subscribe | Hit the 🔔 #SubsetSum #DynamicProgramming #PickNotPick #BooleanDP #GFGPractice #PythonDSA #Memoization #Tabulation #SpaceOptimization #CodeAndDebug #Part202 #InterviewPrep #DPPatterns

Course Hive

Continue this lesson in the app

Install CourseHive on Android or iOS to keep learning while you move.

Related Courses

FAQs

Course Hive
Download CourseHive
Keep learning anywhere