Subset Sum Problem (Dynamic Programming) Theory, Example and Implementation in Python

Veröffentlicht am: 01 Januar 1970
auf dem Kanal: Global Software Support

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In this lecture we are going to discuss another dynamic programming related approach - the subset sum problem 🔥🔥

If you are interested in algorithms such as recursion, selection algorithms, backtracking, dynamic programming and divide-and-conquer approach, then join 'Algorithmic Problems' course! Let's consider the topics one by one:

Section 1 - RECURSION
✔️what are recursion and recursive methods
✔️stack memory and heap memory overview
✔️what is stack overflow?
✔️Fibonacci numbers
✔️factorial function
✔️tower of Hanoi problem

Section 2 - SEARCH ALGORITHMS
✔️linear search approach
✔️binary search algorithm

Section 3 - SELECTION ALGORITHMS
✔️what are selection algorithms?
✔️how to find the k-th order statistics in O(N) linear running time?
✔️quickselect algorithm
✔️median of medians algorithm
✔️the secretary problem

Section 4 - BACKTRACKING
✔️what is backtracking?
✔️n-queens problem
✔️Hamiltonian cycle problem
✔️coloring problem
✔️knight's tour problem

Section 5 - DYNAMIC PROGRAMMING
✔️what is dynamic programming?
✔️knapsack problem
✔️rod cutting problem
✔️subset sum problem

*Section 6 - OPTIMAL PACKING
✔️what is optimal packing?
✔️bin packing problem

*Section 7 - DIVIDE AND CONQUER APPROACHES
✔️what is the divide and conquer approach?
✔️dynamic programming and divide and conquer method
✔️how to achieve sorting in O(NlogN) with merge sort?
✔️the closest pair of points problem

In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together from scratch in Python.

Let's get started!

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