In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

1. •

   Understand the problem statement and business case

2. •

   Import datasets and libraries

3. •

   Perform exploratory data analysis

4. •

   Perform data visualization - part 1

5. •

   Perform data visualization - part 1

6. •

   Prepare the data to feed the clustering model

7. •

   Understand the intuition behind k-means clustering algorithm

8. •

   Find the optimal number of clusters

9. •

   Apply k-means using scikit-learn to perform segmentation

10. •

    Visualize the clusters