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An **algorithm** is a step-by-step set of instructions designed to solve a problem or perform a computation. It serves as the foundation for computer programs, data processing, and automated decision-making.
**Key Characteristics**
1. **Precision** – Must have clear, unambiguous steps.
2. **Finiteness** – Must terminate after a finite number of steps.
3. **Input & Output** – Takes inputs, processes them, and produces outputs.
4. **Effectiveness** – Should be feasible with available resources.
#**Types of Algorithms**
1. **Search Algorithms** (e.g., Binary Search, Linear Search)
2. **Sorting Algorithms** (e.g., QuickSort, MergeSort, Bubble Sort)
3. **Graph Algorithms** (e.g., Dijkstra’s, BFS, DFS)
4. **Machine Learning Algorithms** (e.g., Neural Networks, Decision Trees)
5. **Encryption Algorithms** (e.g., AES, RSA)
#**How Algorithms Work**
1. **Input** → Data is provided (e.g., numbers, text).
2. **Processing** → Algorithm executes logical/mathematical operations.
3. **Output** → Result is returned (e.g., sorted list, shortest path).
#**Applications**
- **Search Engines** (Google’s PageRank)
- **Social Media Feeds** (Facebook, Twitter ranking algorithms)
- **Autonomous Vehicles** (Pathfinding algorithms)
- **Finance** (Algorithmic trading)
#**Example: Binary Search (Pseudocode)** ```plaintext
1. Start with a sorted list and a target value.
2. Compare target with the middle element.
3. If equal, return position.
4. If target is smaller, repeat search on left half.
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