Simple Regression - Fuel Efficiency Prediction

This example replicates the Keras example at https://www.tensorflow.org/tutorials/keras/basic_regression to predict the miles per gallon of a car given its characteristics in the Auto MPG dataset.

MPG Cylinders Displacement Horsepower Weight Acceleration ModelYear Origin
18.0 8 307.0 130.0 3504.0 12.0 70 1
15.0 8 350.0 165.0 3693.0 11.5 70 1
18.0 8 318.0 150.0 3436.0 11.0 70 1
16.0 8 304.0 150.0 3433.0 12.0 70 1
ludwig experiment \
--dataset auto_mpg.csv \
  --config config.yaml

With config.yaml:

training:
    batch_size: 32
    epochs: 1000
    early_stop: 50
    learning_rate: 0.001
    optimizer:
        type: rmsprop
input_features:
    -
        name: Cylinders
        type: number
    -
        name: Displacement
        type: number
    -
        name: Horsepower
        type: number
    -
        name: Weight
        type: number
    -
        name: Acceleration
        type: number
    -
        name: ModelYear
        type: number
    -
        name: Origin
        type: category
output_features:
    -
        name: MPG
        type: number
        optimizer:
            type: mean_squared_error
        num_fc_layers: 2
        output_size: 64