Setting AI Workbench notebook parameters

In the BlueConic AI Workbench, data scientists create AI models in Python and marketing teams can supply data and information to these AI model using a simple graphical UI, without ever having to edit or write any code. For example, for an AI model that calculates a customer score based on different BlueConic profile properties, marketing teams can easily supply these values in the Parameters tab of AI Workbench.

What are parameters for AI marketing models in AI Workbench?

In AI Workbench applications, developers write Python code for AI models. The model might call for a piece of customer data, which segments of user profiles should the model use? Marketers use dropdown menus or text boxes in the Parameters tab of AI Workbench to supply BlueConic data to the AI model.

How do you create notebook parameters?

Developers create notebook parameters in the code of their AI models, in Jupyter notebooks. Developers specify which parameters are used in the code, and they give them a parameter name. For example, the model might use a segment, and marketing teams supply the values they want to use, for example, "Blog Subscribers." The developer would add the following code to the notebook to create a parameter "Customer segment" for the marketing teams to edit:

# Specify parameters 
segment_id = bc.get_blueconic_parameter_value('Customer segment', 'segment')
customer_segment = bc.get_segment(segment_id)

Calling the function get_blueconic_parameter_value() will create the parameter for the marketing team to edit.

How do I set machine learning ai marketing parameters for the machine learning marketing models in BlueConic CDP AI Workbench?

What types of BlueConic values can be a notebook parameter?

Valid parameter types include these types of BlueConic data: channel, connection, date, datetime, dialogue, external_tracker, int (for integer), listener, objective, notebook, profile_property, profile_property_unique, segment, str (for string), and text. For the full list, see the Notebook Parameters API.

How do you edit notebook parameters? 

How do I set ai marketing parameters for marketing machine learning models in BlueConic CDP AI Workbench?

To edit parameters for an AI Workbench application:

  1. In AI Workbench, open the Jupyter notebook that contains your application.
  2. Select the Parameters tab and choose values to supply data to the application.
    For example, in the Customer segment field, the application calls for a BlueConic segment. We chose Blog Subscribers for this value.
  3. Continue selecting values as called for in your application.
  4. Save your settings.
    The next time this notebook runs, it will use the values you supplied.