Chief Data Scientist Jon Krohn discusses big O notation, a fundamental computer science concept that is a prerequisite for understanding almost everything else in data structures, algorithms, and Machine Learning optimization.
Explore three of the most common big O runtimes, constant, linear, and polynomial. The lesson wraps up with an overview of the other common runtimes and performance variation.
This lesson is an excerpt from “Data Structures, Algorithms, and Machine Learning Optimization LiveLessons.” Purchase the entire video course at informit.com/youtube and save 50% with discount code YOUTUBE.
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