Connect the Dots: Factor Analysis
Connect the Dots: Factor Analysis
Factor analysis helps to cut through the clutter when you have a lot of correlated variables to explain a single effect.
This course will help you understand Factor analysis and it’s link to linear regression. See how Principal Components Analysis is a cookie cutter technique to solve factor extraction and how it relates to Machine learning .
What's covered?
Principal Components Analysis
- Understanding principal components
- Eigen values and Eigen vectors
- Eigenvalue decomposition
- Using principal components for dimensionality reduction and exploratory factor analysis.
Implementing PCA in Excel, R and Python
- Apply PCA to explain the returns of a technology stock like Apple
- Find the principal components and use them to build a regression model
Factor extraction using PCA in Excel, R and Python
Url: View Details
What you will learn
- Use Principal Components Analysis to Extract Factors
- Build Regression Models with Principal Components in Excel, R, Python
Rating: 3.75
Level: All Levels
Duration: 1.5 hours
Instructor: Loony Corn
Courses By: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
About US
The display of third-party trademarks and trade names on this site does not necessarily indicate any affiliation or endorsement of hugecourses.com.
View Sitemap