PCA, FA and KMC (ML-02)
The course covers three important topics in Unsupervised Learning: PCA, FA, and KMC
Overview
The course delves into the various techniques of unsupervised machine learning: Principal Component Analysis (PCA), Factor Analysis and K-Means Clustering 9KMC) in a simple and easy-to-understand manner. You will learn the theory, algorithms and a practical case study on these topics using R.
What You Will Learn!
Types of Machine Learning, Linear Algebra, Principal Component Analysis (PCA), Factor Analysis (FA) and K-Means Clustering (KMC)Curriculum
Curriculum
- 1 Section
- 1 Lesson
- 10 Hours
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Course Features
- Lectures 1
- Quizzes 0
- Duration 10 hours
- Skill level All levels
- Language English
- Students 62
- Assessments Yes