Hands-On Predictive Analytics with Python

Building the web application

Finally! It is time for us to build the application that will serve our model's predictions. You can find the full script named predict-diamond-prices.py. Here are the steps we will follow:

1. Make the necessary imports
2. Create the app instance
3. Import an external CSS file
4. Load the trained objects
5. Build the input components and their respective divs
6. Build the prediction function

As always, in Step 1, we begin with the imports:

import dashimport dash_core_components as dccimport dash_html_components as htmlfrom dash.dependencies import Input, Outputfrom keras.models import load_modelfrom sklearn.externals import joblibimport numpy as npimport pandas as pd

Now follow Step 2 and Step 3; create the app instance and import ...