Machine Learning - Factor Analysis

Course

Online

£ 23.79 VAT inc.

*Indicative price

Original amount in USD:

$ 30

Description

  • Type

    Course

  • Level

    Intermediate

  • Methodology

    Online

  • Duration

    Flexible

  • Start date

    Different dates available

Factor extraction using PCA in Excel, R, and Python.
This ’Factor Analysis’ online training course will help you understand Factor Analysis and its 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. Supplemental Materials included!

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Factor analysis helps to cut through the clutter when you have a lot of correlated variables to explain a single effect. In this course, you will follow along with expert instructors to learn about topics such as Mean & Variance, Eigen Vectors, Covariance Matrices, and so much more!

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Reviews

Subjects

  • MS Excel
  • Evaluation
  • Excel
  • Programming
  • Python
  • Data Modeling
  • Factor Analysis
  • Basic Statistics
  • Covariance Matrices
  • Components Analysis
  • Computing Correlation

Teachers and trainers (1)

Name Name

Name Name

Teacher

Course programme

Chapter I: Introduction
  • Lesson I: You, This Course, & Us!
Chapter II: Factor Analysis & PCA
  • Lesson I: Factor Analysis & the Link to Regression
  • Lesson II: Factor Analysis & PCA
Chapter III: Basic Statistics Required for PCA
  • Lesson I: Mean & Variance
  • Lesson II: Covariance & Covariance Matrices
  • Lesson III: Covariance vs Correlation
Chapter IV: Diving into Principal Components Analysis
  • Lesson I: The Intuition Behind Principal Components
  • Lesson II: Finding Principal Components
  • Lesson III: Understanding the Results of PCA – Eigen Values
  • Lesson IV: Using Eigen Vectors to find Principal Components
  • Lesson V: When not to use PCA
Chapter V: PCA in Excel
  • Lesson I: Setting up the data
  • Lesson II: Computing Correlation & Covariance Matrices
  • Lesson III: PCA using Excel & VBA
  • Lesson IV: PCA & Regression
Chapter VI: PCA in R
  • Lesson I: Setting up the data
  • Lesson II: PCA and Regression using Eigen Decomposition
  • Lesson III: PCA in R using packages
Chapter VII: PCA in Python
  • Lesson I: PCA & Regression in Python

Additional information

Highlights:

Understand & Analyze Principal Components
Use Principal Components for dimensionality reduction and exploratory factor analysis
Apply PCA to explain the returns of a technology stock like Apple®
Build Regression Models with Principal Components in Excel, R, & Python


LENGTH

1 hr 45 min

Machine Learning - Factor Analysis

£ 23.79 VAT inc.

*Indicative price

Original amount in USD:

$ 30