Introduction to Clustering using R

Name: Introduction to Clustering using R
Rating: 4.1 (19 reviews)

learn the basics of clustering and R

Created byRajat Raj Aggarwal

Last updated 6/2019

English

What you'll learn

Basics of clustering and R, various clustering techniques, Machine Learning

Course content

7 sections • 42 lectures • 5h 34m total length

Preview, Machine Learning, clustering/classification, supervised/unsupervised6:57
clustering benefits, meaning of unlabeled data4:46
understand clustering using some examples4:19
going through the course content, target audience3:39
Different types of data - continuous/interval & binary5:14
Different types of data - ordinal & nominal data, Scaling the data5:43
create random dataset in R, some datasets used in the course7:00

Using small subset to understand euclidean distance measure4:43
Manually calculating euclidean distance3:52
Randomness in the clustering process5:52
Make two clusters using randomly chosen cluster centroids8:00
make a scatterplot in R using the identified clusters5:57
Introduction to K means clustering, k means function in R, Understanding the out6:16
imdb dataset, Output of k means function, Understanding R codes8:38
recap k means clustering process, Understand R codes11:50
Making clusters using automobile data, Understand R codes, make scatterplot in R11:03
Introduction to manhattan distance, use automobile dataset to calculate manhatta9:08
Formula manhattan distance, visualize the clusters in R11:12

Understand Partitioning Around Medoids Clustering13:39
Introduction to Hierarchical Clustering6:15
Introduction to Single Linkage form of Hierarchical clustering14:28
Complete linkage form of hierarchical clustering6:57
Average linkage form of hierarchical clustering (first method)6:32
Average linkage form of hierarchical clustering (second method)6:22
hclust function in R, Represent clusters using ggplot function13:56
Ward method of Hierarchical clustering, Difference between ward.D and ward.D216:01

Requirements

Some familiarity with statistics

Description

This course would get you started with clustering, which is one of the most well known machine learning algorithm, Anyone looking to pursue a career in data science can use the clustering concepts and techniques taught in this course to gain the necessary skill for processing and clustering any form of data. In addition, the course would familiarize you with R, which is becoming the default programming language for processing data among the global companies.

Who this course is for:

Anyone that wants to make a career in machine learning, research and data analytics

Introduction to Clustering using R

What you'll learn

Explore related topics

Course content

Course Preview, Understanding the Basics of Clustering7 lectures • 38min

Popular distance Measure - Euclidean & Hamming/ Kmeans Clustering in R11 lectures • 1hr 27min

Understand Partitioning Around Medoids, Hierarchical form of Clustering8 lectures • 1hr 24min

Understand clustering process of binary data, Kmodes clustering7 lectures • 49min

Density-based clustering, cluster ordinal data, find replacement for empty cell3 lectures • 28min

Determine ideal number of clusters, daisy function to cluster mixed data5 lectures • 49min

Goodbye1 lecture • 1min

Requirements

Description

Who this course is for: