Python for Programmers

14. Machine Learning: Classification, Regression and Clustering

Objectives

In this chapter you’ll:

• Use scikit-learn with popular datasets to perform machine learning studies.

• Use Seaborn and Matplotlib to visualize and explore data.

• Perform supervised machine learning with k-nearest neighbors classification and linear regression.

• Perform multi-classification with Digits dataset.

• Divide a dataset into training, test and validation sets.

• Tune model hyperparameters with k-fold cross-validation.

• Measure model performance.

• Display a confusion matrix showing classification prediction hits and misses.

• Perform multiple linear regression with the California Housing dataset.

• Perform dimensionality reduction with PCA and t-SNE on the Iris and Digits datasets ...