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Asymptotic Notations: Big O, Big Omega and Big Theta Explained (With Notes)
CodeWithHarry
We 'll talk a little bit about asymptotic notation
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We talked about ordering
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Big O is set to be O ( g ( n ) ) if and only if
there exist a constant ( c ) and a constant n -node such that 0 ≤ f ( n) ≤ cg (n) is O (g (N) If you
watch this video completely then I guarantee that you will understand these three notations
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When we do analysis of
algorithms comparing any 2 algorithms then f ( n ) will be time and what is n , it 's input ok , size
of input
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O ( n²) is Anything Can Be
Algorithm it is g (n) that will be here and which is your algorithm
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If you ca n't find it then its is not f (n ) is O
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