What are the different complexities in algorithms?
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What are the different complexities in algorithms?
Algorithms can have different complexities, primarily categorized as time complexity and space complexity.
Can you explain time complexity in more detail?
Time complexity measures the amount of time an algorithm takes to complete as a function of the input size, often expressed using Big O notation.
What is Big O notation?
Big O notation is a mathematical representation that describes the upper limit of an algorithm's running time, helping to classify its efficiency.
What are some common time complexities I should know?
Common time complexities include O(1) for constant time, O(n) for linear time, O(n^2) for quadratic time, and O(log n) for logarithmic time.
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