Introduction to Algorithm Analysis and Big O Notation
This video introduces algorithm analysis and big O notation. It starts where a previous video leaves off talking about counting operations ( • Tracing Binary Search ) in order to derive a growth rate function T(n). Then we discuss extracting the worst case time complexity of the algorithm O(n) from the growth rate function. Finally, we draw a chart to introduce the most common families of algorithms by time complexity (e.g. constant, logarithm, linear, log linear, etc.)
https://github.com/gsprint23/Cpp-Cras...
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