Udacity: Eigenvectors and Eigenvalues

 with  Ortal Arel
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.

Why Take This Course?
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, called
Principal Component Analysis (PCA).


##Math Refresher

* Vectors
* Linear Transformation

##Definitions and Calculations

* Characteristic Equation of a matrix
* Eigenvalues

##Why is the relevant to Machine Learning?

* Principle Component Analysis (PCA)
0 Student
Cost Free Online Course
Pace Self Paced
Provider Udacity
Language English
Hours 6 hours a week
Calendar 1 weeks long
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What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
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MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

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