Data
Perform an Exploratory Data Analysis
Do you have a large volume of data with multiple variables? Then you need to learn how to perform a multivariate exploratory analysis.
In this course, we will examine ways to efficiently analyze your data using techniques such as Principle Component Analysis, or PCA, which allows you to reduce the number of variables in your dataset while minimizing the amount of information lost.
We will also look at two of the most popular Clustering Methods: the k-means algorithm and hierarchical classification. These enable you to group individuals according to their similarities.
By the end of this course, you will understand when and how to apply these powerful analytical methods to your data.
Objectifs pédagogiques
- Carry out a principal component analysis
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1/2
Table des matières
- Partie 1
Reduce Dimensions in your Data Using Principal Component Analysis
- Partie 2
Find Groups in your Data Using K-Means and Hierarchical Clustering Methods
