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Big O Notations

Get the Code Here: http://goo.gl/Y3UTH MY UDEMY COURSES ARE 87.5% OFF TIL December 19th ($9.99) ONE IS FREE ➡️ Python Data Science Series for $9.99 : Highest Rated & Largest Python Udemy Course + 56 Hrs + 200 Videos + Data Science https://bit.ly/Master_Python_41 ➡️ C++ Programming Bootcamp Series for $9.99 : Over 23 Hrs + 53 Videos + Quizzes + Graded Assignments + New Videos Every Month https://bit.ly/C_Course_41 ➡️ FREE 15 hour Golang Course!!! : https://bit.ly/go-tutorial3 Welcome to my Big O Notations tutorial. Big O notations are used to measure how well a computer algorithm scales as the amount of data involved increases. It isn't however always a measure of speed as you'll see. This is a rough overview of Big O and I hope to simplify it rather than get into all of the complexity. I'll specifically cover the following O(1), O(N), O(N^2), O(log N) and O(N log N). Between the video and code below I hope everything is completely understandable. MY UDEMY COURSES ARE 87.5% OFF TILL MAY 20th ►► New C++ Programming Bootcamp Series for $9.99 : http://bit.ly/C_Course Over 20 Hrs + 52 Videos + Quizzes + Graded Assignments + New Videos Every Month ►► Python Programming Bootcamp Series for $9.99 : http://bit.ly/Master_Python Highest Rated Python Udemy Course + 48 Hrs + 199 Videos + Data Science