Practical Data Science: Reducing High Dimensional Data in R

Online Course

Udemy

What is the course about?
Prerequisites & Facts
Cost, Certificate & Degree
Reviews & Experiences

What is the course about?

Practical Data Science: Reducing High Dimensional Data in R

The course Practical Data Science: Reducing High Dimensional Data in R is an online class provided by Udemy. It may be possible to receive a verified certification or use the course to prepare for a degree.

In this R course, we’ll see how PCA can reduce a 5000+ variable data set into 10 variables and barely lose accuracy!

Course description

Practical Data Science: Reducing High Dimensional Data in R

Understand various ways of reducing wide data sets
Understand Principal Component Analysis (PCA)
Control, tune and measure the effects of PCA
Use GBM modeling to measure the effectiveness of PCA
Reducing dimensionality with classic GBM & GLMNET Variable Selection

Some understanding and interest in the R programming language

2.5 hours on-demand video
8 downloadable resources
Full lifetime access
Access on mobile and TV
Certificate of Completion
Manuel Amunategui

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Prerequisites & Facts

Practical Data Science: Reducing High Dimensional Data in R

Course Topic

Development, ECMAscript, Web Development

University, College, Institution

Udemy

Course Skill Level

see course summary

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

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Degree & Cost

Practical Data Science: Reducing High Dimensional Data in R

To obtain a verified certificate from Udemy you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.

Udemy

Practical Data Science: Reducing High Dimensional Data in R

provided by Udemy

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School: Udemy

Topic: Data Science, Development, R

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