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Algorithms Explained: Computational Complexity

Computational Complexity

algorithm complexity

algorithm run time

time complexity

big O notation

big O

function complexity

linear complexity

loglinear complexity

exponential run time

exponential complexity

O(nlogn)

O(n)

O(2^n)

O(n^2)

O(logn)

polynomial complexity

constant runtime

quadratic run time

algorithm running time

algorithm efficiency

computational efficiency

algorithm speed

memory complexity

theory of computing

O(1)

O(n!)

Автор: DataDaft

Загружено: 12 мар. 2021 г.

Просмотров: 27 961 просмотр

Описание:

An overview of computational complexity including the basics of big O notation and common time complexities with examples of each.

Understanding computational complexity is vital to understanding algorithms and why certain constructions or implementations are better than others. Even if you don't implement algorithms yourself, an understanding of computational complexity can help you better apply the tools you use.

Algorithms Explained: Computational Complexity

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