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Udemy - Principal Component Analysis (PCA) and Factor Analysis

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Name:Udemy - Principal Component Analysis (PCA) and Factor Analysis
Description:

Description

The course explains one of the important aspect of machine learning – Principal component analysis and factor analysis in a very easy to understand manner. It explains theory as well as demonstrates how to use SAS and R for the purpose.

The course provides entire course content available to download in PDF format, data set and code files. The detail course content is as follows.

   Intuitive Understanding of PCA 2D Case
       what is the variance in the data in different dimensions?
       what is principal component?
   Formal definition of PCs
       Understand the formal definition of PCA
   Properties of Principal Components
       Understanding principal component analysis (PCA) definition using a 3D image

   Properties of Principal Components
       Summarize PCA concepts
       Understand why first eigen value is bigger than second, second is bigger than third and so on
   Data Treatment for conducting PCA
       How to treat ordinal variables?
       How to treat numeric variables?
   Conduct PCA using SAS: Understand
       Correlation Matrix
       Eigen value table
       Scree plot
       How many pricipal components one should keep?
       How is principal components getting derived?
   Conduct PCA using R
   Introduction to Factor Analysis
       Introduction to factor analysis
       Factor analysis vs PCA side by side

   Factor Analysis Using R
   Factor Analysis Using SAS
   Theory for using PCA for Variable Selection
   Demo of using PCA for Variable Selection

Who this course is for:

   Analytics Professionals
   Research Scholars
   Data Scientists

Requirements

   The course will start with elementary concepts but knowledge of basic statistics will help
   For execution – it will help to know basic SAS or R programming

Last Updated 6/2018
YouTube Video:
Category:Tutorials
Language:English  English
Total Size:287.35 MB
Info Hash:389E645BAD833984EB330F0652DD3D1746A8D61E
Added By:tutsnode Verified UploaderVIP
Date Added:2020-12-26 23:11:23
Torrent Status:Torrent Verified


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