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
Download Links
Direct Download
Principal Component Analysis (PCA) and Factor Analysis.zip (280.8 MB) | Mirror
Torrent Download
Principal Component Analysis (PCA) and Factor Analysis.torrent (32 KB) | Mirror
Source : https://www.udemy.com/course/principal-component-analysis-pca-and-factor-analysis/
