Big O notation is simpler than you might think
Big O notation is a very popular topic, in contexts such as algorithms and P vs NP. In this video, I attempt to explain big O notation using only basic arithmetic, so that these other topics can be enjoyed by everyone! Timestamps: Intro: 00:00 Eventuality: 00:28 Deltas: 03:54 Stolz-Ces
From playlist Summer of Math Exposition Youtube Videos
From playlist Algorithms 1
Big O Part 4 – Logarithmic Complexity
The raw performance of an algorithm, program, or a programmatic operation depends on a number of factors such, not least the computer it’s running on. Big O is not concerned with this; Big O describes the way the time taken by a program (or memory or space usage) depends on the amount of
From playlist Big O Complexity
Introduction to Big-O Notation
This video introduces Big-O notation. http://mathispower4u.com
From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)
Big O Part 3 – Quadratic Complexity
The raw performance of an algorithm, program, or a programmatic operation depends on a number of factors such, not least the computer it’s running on. Big O is not concerned with this; Big O describes the way the time taken by a program (or memory or space usage) depends on the amount of
From playlist Big O Complexity
Big O Part 6 – Summary of Time Complexities
The raw performance of an algorithm, program, or a programmatic operation depends on a number of factors such, not least the computer it’s running on. Big O is not concerned with this; Big O describes the way the time taken by a program (or memory or space usage) depends on the amount of
From playlist Big O Complexity
From playlist Algorithms 1
Big O Notation: A Few Examples
This video is about Big O Notation: A Few Examples Time complexity is commonly estimated by counting the number of elementary operations (elementary operation = an operation that takes a fixed amount of time to preform) performed in the algorithm. Time complexity is classified by the nat
From playlist Computer Science and Software Engineering Theory with Briana
Introduction to Big-Omega Notation
This video introduces Big-Omega notation. http://mathispower4u.com
From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)
Comparing Algorithms: Big O Notation
In this video we look at to how to compare ressource requirements of algorithms, independently from hardware, implementation etc. In doing so we will come across a useful, but infamous tool from the field of algorithms: big O notation 00:00 Ressource requirements and the scalability of al
From playlist All About Algorithms
Lecture 2 - Asymptotic Notation
This is Lecture 2 of the CSE373 (Analysis of Algorithms) taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 1997. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/1997/lecture2.pdf
From playlist CSE373 - Analysis of Algorithms - 1997 SBU
Lec 2 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005
Lecture 02: Asymptotic Notation | Recurrences | Substitution, Master Method View the complete course at: http://ocw.mit.edu/6-046JF05 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503),
CSE373 2012 - Lecture 02 - Big-O Notation (Asymptotic Notation)
This is Lecture 2 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 2012.
From playlist CSE373 - Analysis of Algorithms - 2012 SBU
In this video, we are trying to get a better intuition for what it means if some algorithm has particular time or space requirements in big O notation. In doing so, we will learn what time complexity means, look at typical running times of algorithms and consider if there might be alternat
From playlist All About Algorithms
Big O Notation : Data Science Basics
A coding interview question to explain Big O Notation! Gaussian sum formula: https://www.mathwords.com/a/arithmetic_series.htm
From playlist Data Science Basics
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, li
From playlist Talks and Tutorials
MountainWest JavaScript 2015 - Essential Big O for JavaScript Developers by Dave Smith
Essential Big O for JavaScript Developers by Dave Smith What every JavaScript developer should know about Big O notation. Computer science can be intimidating, and Big O is no exception. Let’s break it down. Understanding the time complexity of common JavaScript operations can make your c
From playlist MWJS 2015
Truly Understanding Big O Notation: An introduction to analysing algorithm efficiency #SoME2
Understand the basics of analysing algorithms using big O notation, big Omega notation and Theta notation. Here are some related videos: - Truly Understanding Bubble Sort: https://www.youtube.com/watch?v=JVilYn7kiIc - Truly Understanding Merge Sort: https://www.youtube.com/watch?v=HpPr0t8
From playlist Summer of Math Exposition 2 videos
Big O Part 1 – Linear Complexity
The raw performance of an algorithm, program, or a programmatic operation depends on a number of factors such, not least the computer it’s running on. Big O is not concerned with this; Big O describes the way the time taken by a program (or memory or space usage) depends on the amount of
From playlist Big O Complexity