List of Listings

 

Chapter 1. Learning reactive machine learning

Listing 1.1. A simple model

Listing 1.2. A Pooch Predictor model

Chapter 2. Using reactive tools

Listing 2.1. A map of votes

Listing 2.2. Handling no votes using pattern matching

Listing 2.3. Setting default values on maps

Listing 2.4. A remote “database”

Listing 2.5. Futures-based remote calls

Listing 2.6. Futures-based timeouts

Listing 2.7. An unreliable database

Listing 2.8. A vote case class

Listing 2.9. A vote-writing actor

Listing 2.10. A supervisory actor

Listing 2.11. Full voting app

Listing 2.12. Basic Spark setup

Listing 2.13. Handling the data path

Listing 2.14. Loading training and testing data

Listing 2.15. Training a model

Listing 2.16. Testing a model

Listing 2.17. Model metrics

Listing 2.18. Saving a model

Chapter 3. Collecting data

Listing 3.1. Calculating location densities

Listing 3.2. Aggregating regional densities

Listing 3.3. Concurrently accessible densities

Listing 3.4. In-order updates

Listing 3.5. Out-of-order updates

Listing 3.6. Sensor-readings case class

Listing 3.7. Creating sensor-reading documents

Listing 3.8. Creating a sensor ID view

Listing 3.9. All records for a sensor

Listing 3.10. Inserting many random records

Listing 3.11. A time-based view of sensor readings