Eigenvectors and Eigenvalues (Udacity)

Eigenvectors and Eigenvalues (Udacity)
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Eigenvectors and Eigenvalues (Udacity)
Concepts in Linear Algebra. One of the most interesting topics to visualize in Linear Algebra are Eigenvectors and Eigenvalues. Here you will learn how to easily calculate them and how they are applicable and particularly interesting when it comes to machine learning implementations.

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In the computational world of AI you will often encounter enormous amounts of data that needs to be processed. Often, the data volume will be so large that you will need to use some form of data reduction technique. Eigen-concepts are a big part of the mathematical background needed to understand a useful data reduction tools, calledPrincipal Component Analysis (PCA).


What you will learn


Vectors

- Linear Transformation


Definitions and Calculations

- Characteristic Equation of a matrix

- Eigenvalues

- Eigenvectors


Why is the relevant to Machine Learning?

- Principle Component Analysis (PCA)


Prerequisites and requirements

To easily understand this class you will need to have mathematical background in Linear Algebra. Refresh your memory or go over the topics of Linear transformation , Determinants And a System of linear equations before beginning.



MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Free Course

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.