Real-World Machine Learning

List of Listings

Chapter 1. What is machine learning?

Listing 1.1. Initial structure of an ML workflow program

Listing 1.2. Our ML workflow program with model evaluation

Chapter 2. Real-world data

Listing 2.1. Convert categorical features to numerical binary features

Listing 2.2. Simple feature extraction on Titanic cabins

Listing 2.3. Feature normalization

Chapter 3. Modeling and prediction

Listing 3.1. Building a logistic regression classifier with scikit-learn

Chapter 4. Model evaluation and optimization

Listing 4.1. Cross-validation with the holdout method

Listing 4.2. Cross-validation with k-fold cross-validation

Listing 4.3. The ROC curve

Listing 4.4. The area under the ROC curve

Listing 4.5. The root-mean-square error

Listing 4.6. ...