0/1 Knapsack Problem Explained Visually

Details

Description

In this video, we dive deep into the 0/1 Knapsack Problem using dynamic programming. We start by building a table to track the maximum profit achievable for different knapsack capacities.
Then, we fill the table step by step, explaining how to include or exclude items based on their weight and profit.
Finally, we backtrack through the table to determine which items are included in the optimal solution.

By the end of this video, you'll understand:
✅ How to construct and fill the DP table
✅ How to find the selected items efficiently
✅ The time and space complexity of the approach



📌 Topics Covered:

0:00 Introduction ✅
0:43 Naïve Approach and its pitfalls ✅
1:12 Dynamic Programming Approach ✅



video on Fractional Knapsack problem (greedy method):- https://youtu.be/ujHQlfR3qfo

video on introduction to Dynamic Programming:- https://youtu.be/9uusvK3HRk0

code for animations:-https://github.com/ByteQuest0/Animation_codes/tree/main/2025/Knapsack

code (GitHub) for implementation:-https://github.com/ByteQuest0/Implemention_codes/blob/main/Dynamic%20Programming/knapsack.py

Tools used to make this video:- ManimGL (python library for animation), Premier Pro for video editing, a TTS tool.