Voltar para Customer Segmentation using K-Means Clustering in R
Comentários e feedback de alunos de Customer Segmentation using K-Means Clustering in R da instituição Coursera Project Network
Sobre o curso
Welcome to this project-based course, Customer Segmentation using K-Means Clustering in R. In this project, you will learn how to perform customer market segmentation on mall customers data using different R packages.
By the end of this 2-and-a-half-hour long project, you will understand how to get the mall customers data into your RStudio workspace and explore the data. By extension, you will learn how to use the ggplot2 package to render beautiful plots of the data. Also, you will learn how to get the optimal number of clusters for the customers' segments and use K-Means to create distinct groups of customers based on their characteristics. Finally, you will learn how to use the R markdown file to organise your work and how to knit your code into an HTML document for publishing.
Although you do not need to be a data analyst expert or data scientist to succeed in this guided project, it requires a basic knowledge of using R, especially writing R syntaxes. Therefore, to complete this project, you must have prior experience with using R. If you are not familiar with working with using R, please go ahead to complete my previous project titled: “Getting Started with R”. It will hand you the needed knowledge to go ahead with this project on Customer Segmentation. However, if you are comfortable with working with R, please join me on this beautiful ride! Let’s get our hands dirty!
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1 — 1 de 1 Avaliações para o Customer Segmentation using K-Means Clustering in R
por Oksana B
•28 de Nov de 2021
Save your 10 bucks and watch some videos on youtube on the subject. Poorly prepared project. Instructor does not explain the outputs that the function produce. I am under the impression he does not know how to explain The Gap Statistics output. And one more thing: this is NOT an intermediate level. This is a beginner's level. Very disappointed.
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