Asymptotic Notation Solved Examples | Part-5 | Big O | Big Ω | Big Θ | GATECSE | DAA

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This video explores Big O notation, a fundamental tool for computer scientists and software engineers to analyze algorithm costs. Big O notation is used to measure the growth of a program's running time or space requirements as input size increases. It is a mathematical way to measure time complexity, considering only the fastest growing term and discarding other terms and constants. It is also used to measure space complexity. The video provides examples of how to find the Big O runtime of various algorithms and helps users evaluate and discuss the performance of different solutions to the same problem.
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[@aryansrivastava1348]

12:12 respect tends to infinity for your dedication sir (aapka paseena dikh rha hai hum logo ko😅🥲)

[@saniyaabbasi8037]

Very well explained !

[@anuragjain7250]

Yes sir smjh mai aagaya

[@sunilpatidar8609]

best content

[@aparnakumari5570]

super👌

[@anawarkhan2938]

👍

[@raghavendra1563]

Sir, I have a small doubt, Is the below equation true?? if f(n) E O (n^3) then f(n) + 10n^2 = theta (n^3) ???? Here E is belongs to ^ --> power of O --> Big O Please clarify sir, because if we take f(n) as any polynomial of n^3, this hold good but if we take f(n) as poylonimal of degree2, this might fail

[@anonymous10906]

its false

[@a8488vv]

Mujhe aapke videos phle kyo nhi mile😢

[@muskanyadav7362]

Same 😭