Let’s look at a problem from the Chapter 6 MyLab assignment where we can calculate Euclidean distance.
Section Exercises
Example 6.1. Euclidean Distance.
Example 6.2. k-Means Clustering in Tableau.
Use Tableau to do k-means clustering in the following examples:
- Salary Data:
external/sheets/Salary_Data.csv - Online Retail Data:
https://bit.ly/4c7cMVl
Example 6.3. k-Means Clustering.
Let’s look at a problem involving k-means clustering from the Chapter 6 MyLab assignment.
Example 6.4. Hierarchical Clustering.
Let’s look at a problem involving hierarchical clustering from the Chapter 6 MyLab assignment.
Example 6.5. Association Rules for Hy-Vee.
Let’s apply the ideas we learned about association rules to the Hy-Vee data files:
Example 6.6. Apriori Algorithm in Python.
If we have time, we can see how to implement the \textbf{Apriori algorithm} to automate the process for analyzing transaction data in Python:
Example 6.7. Additional Clustering Example using Generative AI.
Let’s use the gender inequality index data that can be found at the link below, and see some additional ways we can leverage generative AI to cluster countries based on this data.
Example 6.8. Sentiment Analysis Example: Classifying Product Reviews.
(Remember that this is an example of predictive analytics instead of descriptive analytics, which we focus on in this class.)
Example 6.9. Visualizing Text Data.
Let’s see how to create a word cloud in Tableau and see when it might be helpful.
