Course Content

Clustering Demystified

Introduction Import Necessary Libraries and Data Preliminary Analysis Data Preparation Declare Feature Vector and Target Variable Convert Categorical Variable into Integers Feature Scaling K-Means Model with 2 Clusters Check the Quality How many Clusters?K-Means Model with 4 Clusters

Clustering Demystified

K-Means Model with 4 Clusters

Let's try to improve clustering results using the split on 4 separate clusters.

The task is completed!

TaskCompleted

Evaluate the KMeans with 4 clusters.
Fit the algorithm.

Congratulations on completing the Clustering Project!

Everything was clear?

Section 1. Chapter 11

Course Content

Clustering Demystified

Introduction Import Necessary Libraries and Data Preliminary Analysis Data Preparation Declare Feature Vector and Target Variable Convert Categorical Variable into Integers Feature Scaling K-Means Model with 2 Clusters Check the Quality How many Clusters?K-Means Model with 4 Clusters

Clustering Demystified

K-Means Model with 4 Clusters

Let's try to improve clustering results using the split on 4 separate clusters.

The task is completed!

TaskCompleted

Evaluate the KMeans with 4 clusters.
Fit the algorithm.

Congratulations on completing the Clustering Project!

Everything was clear?

Section 1. Chapter 11

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