Algorithms are step-by-step computational procedures for solving problems — ranging from simple tasks like searching and sorting to complex optimization and graph traversal challenges. They form the foundation of computer science, enabling efficient data processing across fields like artificial intelligence, databases, networking, and systems design. Understanding algorithmic paradigms — such as divide-and-conquer, dynamic programming, greedy methods, and backtracking — equips you to select the right strategy for a problem's constraints. A key insight: the best algorithm isn't always the fastest in theory; cache locality, constant factors, and input characteristics often matter more in practice than asymptotic complexity alone.

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