Practical Data Science: Reducing High Dimensional Data in R

Online Course

Udemy
Practical Data Science: Reducing High Dimensional Data in R

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

Prerequisites & Facts

Practical Data Science: Reducing High Dimensional Data in R

Course Topic

Data Science, Development, R

University, College, Institution

Udemy

Course Skill Level

Course Language

English

Place of class

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

Degree

Certificate

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