Putting It All Together
Combine data preparation, model training, and user interface to build a machine learning modeling pipeline.
We'll cover the following
Components needed for a modeling pipeline
We now have all the components needed for our end-to-end modeling pipeline.
Training data
Data preprocessing
Model trained
User interface to interact with the model
Function to connect the user interface to the trained model
We will now combine all this together, and assign an Event Listener to trigger the inference.
Modeling application: Putting it all together
In this lesson, we will attach an Event Listener to the button. Recall that an Event Listener has three components: a function, input, and output.
In this case, our inputs will be all components that the user has interacted with to set attribute values for the prediction. This will be passed into the function predict_price()
, which will use the trained model to make an inference about the price. Finally, this will be displayed in the output component, which is set as a textbox below the button.
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