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