YoVDO

Connect the Dots: Factor Analysis

Offered By: Udemy

Tags

Principal Components Analysis Courses Machine Learning Courses Python Courses Linear Regression Courses Factor Analysis Courses Eigenvalues Courses Eigenvectors Courses Regression Models Courses

Course Description

Overview

Factor extraction using PCA in Excel, R and Python

What you'll learn:
  • Use Principal Components Analysis to Extract Factors
  • Build Regression Models with Principal Components in Excel, R, Python

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 youunderstand Factoranalysis and it’s link to linear regression. See how Principal Components Analysis is a cookie cutter technique to solve factor extraction and how itrelates toMachine learning .

What's covered?

Principal Components Analysis

  • Understanding principal components
  • Eigen values and Eigen vectors
  • Eigenvaluedecomposition
  • 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

Taught by

Loony Corn

Related Courses

Structural Equation Model and its Applications | 结构方程模型及其应用 (普通话)
The Chinese University of Hong Kong via Coursera Applied Multivariate Statistical Modeling
Indian Institute of Technology, Kharagpur via Swayam Structural Equation Model and its Applications | 结构方程模型及其应用 (粤语)
The Chinese University of Hong Kong via Coursera Survey analysis to Gain Marketing Insights
Emory University via Coursera Business Analytics and Digital Media
Indian School of Business via Coursera