Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud

Exercises

1. 15.1 (Using PCA to Help Visualize the Digits Dataset) In this chapter, we visualized the Digits dataset’s clusters. To do so, we first used scikit-learn’s TSNE estimator to reduce the dataset’s 64 features down to two, then plotted the results using Seaborn. Reimplement that example to perform dimensionality reduction using scikit-learn’s PCA estimator, then graph the results. How do the clusters compare to the diagram you created in the clustering case study?

2. 15.2 (Using TSNE to Help Visualize the Iris Dataset) In this chapter, we visualized the Iris dataset’s clusters. To do so, we first used scikit-learn’s PCA estimator to reduce the dataset’s four features down to two, then plotted the results using Seaborn. Reimplement that example ...