Types of algorithms

1. Search Algorithms

• Linear Search: Sequentially checks each element until the desired value is found.
• Binary Search: Efficiently searches a sorted list by dividing the search range in half.

2. Sorting Algorithms

• Bubble Sort: Repeatedly swaps adjacent elements to sort a list.
• Merge Sort: Divides the list, sorts each part, and merges them.
• Quick Sort: Sorts by selecting a pivot and partitioning the elements around it.
• Heap Sort: Builds a heap to repeatedly extract the largest or smallest element.

3. Dynamic Programming Algorithms

• Fibonacci Sequence: Computes Fibonacci numbers by storing intermediate results.
• Knapsack Problem: Maximizes the total value while staying within a weight limit.
• Longest Common Subsequence (LCS): Finds the longest subsequence common to two sequences.

4. Greedy Algorithms

• Dijkstra’s Algorithm: Finds the shortest path from a source node in a graph.
• Prim’s Algorithm: Builds a minimum spanning tree by choosing the smallest edge.

5. Divide and Conquer Algorithms

• Merge Sort: Divides, sorts, and merges data for efficient sorting.
• Quick Sort: Similar to Merge Sort but uses a pivot for partitioning.
• Binary Search: Recursively divides the search range.

6. Backtracking Algorithms

• N-Queens Problem: Places queens on a chessboard so no two threaten each other.
• Sudoku Solver: Attempts values in empty cells and backtracks when necessary.
• Hamiltonian Path: Finds a path visiting each vertex exactly once.

7. Machine Learning Algorithms

• Linear Regression: Models relationships between variables for predictions.
• K-Means Clustering: Groups data points into clusters based on similarity.
• Q-Learning: Learns optimal actions in dynamic environments.

8. Encryption Algorithms

• AES (Advanced Encryption Standard): Encrypts data securely with symmetric keys.
• RSA (Rivest–Shamir–Adleman): Asymmetric encryption using public and private keys.
• SHA (Secure Hash Algorithm): Generates fixed-length hashes for data integrity.

9. Graph Algorithms

• Kruskal’s Algorithm: Builds a minimum spanning tree using edge weights.
• Floyd-Warshall Algorithm: Computes shortest paths between all graph nodes.
• Bellman-Ford Algorithm: Finds shortest paths, even with negative weights.

10. String Matching Algorithms

• Knuth-Morris-Pratt (KMP): Matches strings using a partial match table.
• Rabin-Karp: Uses hashing for efficient pattern matching.
• Boyer-Moore: Searches from right to left to skip unnecessary comparisons.

11. Randomized Algorithms

• Monte Carlo Algorithm: Uses randomness for approximate solutions.
• Las Vegas Algorithm: Guarantees correct results but uses random steps.
• Quick Sort (Random Pivot): Chooses random pivots to avoid worst-case scenarios.

12. Recursive Algorithms

• Factorial Calculation: Computes n! by multiplying recursively.
• Tower of Hanoi: Solves disk transfer problems recursively.
• Binary Tree Traversals: Visits tree nodes in a specific recursive order.

13. Approximation Algorithms

• Traveling Salesman Problem (TSP): Finds near-optimal routes efficiently.
• Vertex Cover Problem: Selects minimum vertices to cover all graph edges.

14. Brute Force Algorithms

• Password Cracking: Tries all combinations until the correct one is found.
• Subset Sum Problem: Checks all subsets to find one meeting a condition.

15. Evolutionary Algorithms

• Genetic Algorithms: Uses natural selection principles to find solutions.
• Particle Swarm Optimization: Simulates swarm behavior to optimize functions.