Deep Learning with JavaScript

List of Listings

Chapter 2. Getting started: Simple linear regression in TensorFlow.js

Listing 2.1. Hard-coding the training and test data (from CodePen 2-a)

Listing 2.2. Converting data into tensors (from CodePen 2-b)

Listing 2.3. Constructing a linear regression model (from CodePen 2-c)

Listing 2.4. Configuring training options: model compilation (from CodePen 2-c)

Listing 2.5. Fitting a linear regression model (from CodePen 2-c)

Listing 2.6. Model definition, training, evaluation, and prediction

Listing 2.7. Converting the Boston-housing data to tensors in index.js

Listing 2.8. Calculating baseline loss of guessing the mean price

Listing 2.9. Data normalization: zero mean, unit standard deviation

Listing 2.10. Defining a linear-regression ...