Applied data mining

Path analysis (computing)

Path analysis, is the analysis of a path, which is a portrayal of a chain of consecutive events that a given user or cohort performs during a set period of time while using a website, online game, or eCommerce platform. As a subset of behavioral analytics, path analysis is a way to understand user behavior in order to gain actionable insights into the data. Path analysis provides a visual portrayal of every event a user or cohort performs as part of a path during a set period of time. While it is possible to track a user's path through the site, and even show that path as a visual representation, the real question is how to gain these actionable insights. If path analysis simply outputs a "pretty" graph, while it may look nice, it does not provide anything concrete to act upon. (Wikipedia).

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Critical Paths Analysis (1) - Precedence Tables

Powered by https://www.numerise.com/ Critical Paths Analysis (1) Decision Maths 1 Edexcel A-Level Maths.

From playlist Decision Maths - Critical Paths Analysis

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Find the Shortest Path - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

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Graph Data Structure 6. The A* Pathfinding Algorithm

This is the sixth in a series of videos about the graph data structure. It includes a step by step walkthrough of the A* pathfinding algorithm (pronounced A Star) for a weighted, undirected graph. The A* pathfinding algorithm, and its numerous variations, is widely used in applications suc

From playlist Path Finding Algorithms

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Quadratic Function

The Video going to guide how to make quadratic function with graph. lets see the video to make it, it's easy.

From playlist CALCULUS

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Critical Paths Analysis (4) - Early Start & Late Finish Times

Powered by https://www.numerise.com/ Critical Paths Analysis (4) Decision Maths 1 Edexcel A-Level Maths

From playlist Decision Maths - Critical Paths Analysis

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What is a Path Graph? | Graph Theory

What is a path graph? We have previously discussed paths as being ways of moving through graphs without repeating vertices or edges, but today we can also talk about paths as being graphs themselves, and that is the topic of today's math lesson! A path graph is a graph whose vertices can

From playlist Graph Theory

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24C3: I know who you clicked last summer

Speaker: Svenja Schröder A swiss army knife for automatic social investigation This talk introduces some techniques of social network analysis and graph theory. It aims at using simple approaches for getting interesting facts about networks. I will use the data of a popular community t

From playlist 24C3: Full steam ahead

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Aaron Sidford: Introduction to interior point methods for discrete optimization, lecture II

Over the past decade interior point methods (IPMs) have played a pivotal role in mul- tiple algorithmic advances. IPMs have been leveraged to obtain improved running times for solving a growing list of both continuous and combinatorial optimization problems including maximum flow, bipartit

From playlist Summer School on modern directions in discrete optimization

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Marcelo Frias: Relational tight field bounds for distributed analysis of programs

HYBRID EVENT Recorded during the meeting "19th International Conference on Relational and Algebraic Methods in Computer Science" the November 3, 2021 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other t

From playlist Virtual Conference

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Dan Crisan: Cubature methods and applications

Abstract: The talk will have two parts: In the first part, I will go over some of the basic feature of cubature methods for approximating solutions of classical SDEs and how they can be adapted to solve Backward SDEs. In the second part, I will introduce some recent results on the use of c

From playlist Probability and Statistics

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An Improved Exponential-Time Approximation Algorithm for Fully-Alternating Games... - Andrew Drucker

Computer Science/Discrete Mathematics Seminar I Topic: An Improved Exponential-Time Approximation Algorithm for Fully-Alternating Games Against Nature Speaker: Andrew Drucker Affiliation: University of Chicago Date: January 25, 2021 For more video please visit http://video.ias.edu

From playlist Mathematics

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Noise Sensitivity and Chaos in Random Planar Geometry by Shirshendu Ganguly

PROGRAM : FIRST-PASSAGE PERCOLATION AND RELATED MODELS (HYBRID) ORGANIZERS : Riddhipratim Basu (ICTS-TIFR, India), Jack Hanson (City University of New York, US) and Arjun Krishnan (University of Rochester, US) DATE : 11 July 2022 to 29 July 2022 VENUE : Ramanujan Lecture Hall and online T

From playlist First-Passage Percolation and Related Models 2022 Edited

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Aaron Sidford: Introduction to interior point methods for discrete optimization, lecture III

Over the past decade interior point methods (IPMs) have played a pivotal role in mul- tiple algorithmic advances. IPMs have been leveraged to obtain improved running times for solving a growing list of both continuous and combinatorial optimization problems including maximum flow, bipartit

From playlist Summer School on modern directions in discrete optimization

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Neža Mramor (2/17/21): An application of discrete Morse theory to robot motion planning

Title: An application of discrete Morse theory to robot motion planning Abstract: We will shortly recollect the basics of discrete Morse theory and two of its variants, parametric and fiberwise discrete Morse theory. We will then describe how it can be used to construct a continuous motio

From playlist AATRN 2021

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4 Motion part 2

In this second part on Motion, we take a look at calculating the velocity and position vectors when given the acceleration vector and initial values for velocity and position. It involves as you might imagine some integration. Just remember that when calculating the indefinite integral o

From playlist Life Science Math: Vectors

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Why Do I Need to Know Python -- I'm a Pandas User || James Powell

It's common for data scientists to narrowly focus on the APIs of the tools they use every day—pandas, matplotlib, pymc, dask, &c.—to the detriment of any focus on the surrounding programming language. In the case of tools like matplotlib, the total amount of Python we need to know is limit

From playlist Python

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Tangent Line of Curve Parallel to A Line Calculus 1 AB

I work through an example to explain how to find tangent lines to a function that are parallel to a given line. Find free review test, useful notes and more at http://www.mathplane.com If you'd like to make a donation to support my efforts look for the "Tip the Teacher" button on my channe

From playlist Calculus

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Alice Le Brigant : Information geometry and shape analysis for radar signal processing

Recording during the thematic meeting : "Geometrical and Topological Structures of Information" the August 31, 2017 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent

From playlist Geometry

Related pages

Behavioral analytics | Statistics | Data mining | Big data