Machine Learning Examples for Data Science in R

Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level

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Overview/Description
R is a free software environment for statistical computing and graphics and has become an important tool in modern data science. In this course, you will learn the essential R machine learning methods that data scientists use in their everyday work.

Target Audience
Individuals with some statistics, programming, and machine learning experience who wish to learn machine learning methods in R used in data science in R

Prerequisites
None

Expected Duration (hours)
2.5

Lesson Objectives

Machine Learning Examples for Data Science in R

start the course

distinguish between supervised and unsupervised learning

perform classical multidimensional scaling using cmdscale in R

perform hierarchical cluster analysis in R

use the corclust function in the klaR package in R

perform k-means clustering on data in R

use the kselection package to select k for a k-means clustering in R

use the clusplot function to perform a cluster plot on a clara object in R

perform a fully C-Means clustering from the e1071 package in R

create a basic classification tree using rpart in R

create a basic regression tree using rpart in R

create a basic classification tree with the trees package in R

create a basic regression tree with the trees package in R

perform a K-Nearest Neighbor classification in R

use the randomforest package for classification in R

combine random forest ensembles into a single object in R

use random forests for unsupervised classification in R

use the clusplot function to perform a cluster plot on a pam cluster in R

build a naïve bayes classifier using the klaR package in R

use the lda function in R

use the qda function from the MASS package in R

perform a MDS using the mda package in R

use the SVM function from the e1071 library in R

perform a curve fit using the LOESS method in R

perform a PLS regression using the pls package in R

plot a smoothing spline from the splines packages in R

use the boosting function from the adabag package in R

use the bagging function from the adabag package in R

create a scatterplot matrix using the caret package in R

create an overlayed density plot using the caret package in R

create a 3D Scatterplot in R

provide a basic understanding of how to use common statistical methods for data analysis in R

Course Number:
df_dsfd_a02_it_enus

Expertise Level
Intermediate