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Understanding Algorithms: The Blueprint of Problem-Solving

  • Efficient algorithms are crucial for solving problems quickly and with minimal resources.
  • Big O notation provides an upper bound on the time complexity of an algorithm.
  • Common algorithm complexities ranked from best to worst include linear search, binary search, selection sort, bubble sort, and merge sort.
  • Algorithms exist not only in computing but also in nature and biology, influencing processes such as biochemical regulation in the human body and decision-making in animals.

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