Knapsack beginner python

Certainly! The knapsack problem is a classic optimization problem that deals with selecting items to maximize the total value within a given weight constraint. There are two variations: the 0/1 knapsack problem, where items cannot be divided, and the fractional knapsack problem, where items can be divided to fill the knapsack.
In this tutorial, we'll cover the 0/1 knapsack problem using Python.
Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit, and the total value is maximized.
We'll solve the 0/1 knapsack problem using dynamic programming with a bottom-up approach.
For the example provided in the code, with weights [10, 20, 30], values [60, 100, 120], and a knapsack capacity of 50, the output will be the maximum value 220 and the selected items [1, 2] (indices 1 and 2 in the input lists).
This tutorial provides a basic understanding of solving the 0/1 knapsack problem in Python. You can modify the input arrays and the knapsack capacity to see how the algorithm works for different scenarios.
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