Algorithms

A collection of some of the most frequently used Algorithms and advanced algorithms in C++ (cause it's efficent) and Python (cause I love it). This repository consists of a large collection of algorithms.

Updates

I keep updating it from time to time (too frequently)

Contents

1. Merge Sort
2. Greedy Fractional Knapsack
3. Breadth First Search
4. Depth First Search
5. Binary Search
6. Chain Matrix Multiplication (Dynamic Programming)
7. Floyd Warshall (Dynamic Programming)
8. Fibonacci Series (Dynamic Programming)
9. Bellman Ford Single Source Shortest Path
10. Inorder Preorder and Postorder Traversal
11. Determinant Computation
12. Local Minima (Divide and Conquer)
13. Bitonic Point in Bitonic Series (Divide and Conquer)
14. Closest Pair Problem (Divide and Conquer)
15. Find Smallest Element in increasing sequence rotated unknown number of times and rotation number (Algorithm-Jeff Erickson P-60 Q33)
16. Smallest Element Find in Decreasing then Increasing Sequence (Divide and Conquer)
17. Smallest Element Find in Bitonic Sequence (Algorithm-Jeff Erickson P-60 Q30)
18. Row Reduced Edchelon Form using Row Echelon Form
19. Maximum Sub Array Sum Problem (Divide and Conquer)
20. Maximum Sub Array Sum Problem (Kadane's Algorithm)
21. FInd A[i] = i in a sorted array (Algorithm-Jeff Erickson P-60 Q31)
22. QuickSort Alogorithm
23. Fast Perfect Cube Check Algorithm
24. Fast Power Raise Algorithm in O(logn)
25. Fast Kth Root of Element Find in O(logn)
26. Rabin Karp Algorithm for String Matching O(m+n)
27. Inversion Count in Array O(nlogn)
28. Find Kth Smallest Element in Unsorted Array O(logn)
29. Kth Smallest Element in Union of two Sorted Array O(n)
30. K Closest Elements in Array from First Element of Array O(n)
31. Gram-Schmidt Orthogonalization of a (m x n) matrix
32. Least Recently Used (LRU) Greedy Algorithm