Uploading Single Custom Models

Overview

You can integrate your artificial intelligence and machine learning models deployed as web service endpoints to utilize unified tables. Predictions create better customer experiences, for example, predictions on unified customer profiles and activities. It improves business capabilities and revenue streams.
SkyPoint creates new dimensions for understanding and segmenting your customers into high-performing audiences. SkyPoint Modern Data Stack Platform (MDSP) imports and unifies the data that you can upload for custom integration.

Prerequisites

To configure the Custom model, the following prerequisites must be met:

• You must have an API of the custom object to make the import request.
• Request and response body of the service should be in JSON format.

To add a Single Custom model

Follow the below steps to send your data to the custom model and brings the output:

1. In the left pane, go to Predict > Custom.
   The Custom models window appears.

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2. Click New workflow.

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3. Select Single upload.
4. In the Name box, enter your custom model web service.
5. Enter the web address of the API name of the custom object in the URL box.
6. Select the Hypertext Transfer Protocol (HTTP) method from the URL Method drop-down list.

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URL method	Description
GET	Requests retrieve data from the server.
POST	Sends data to the server.
PUT	Replaces all current data of the target resource with the uploaded content.
DELETE	Removes the resource.

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7. Click Add Row to enter the header key and value.
8. Enter JSON code in the Body area to pass the data.
9. Enter the score path to map web service output.

Note

When you run the custom model, the platform makes an HTTP call to the service with the required parameters and retrieves the output. You also need to specify the path of the score property in your JSON response. The notation is very similar to the JavaScript notation of parsing properties.

• An Array is an ordered list of values. For Array, square brackets should be used. The Array properties indices start from 0 and are accessible with the '[]' operator.
• An object is a collection of key values. For object, curly brackets should be used. Key always be enclosed in double quotes. The Object type properties are accessible with a "." operator.

For example, this is the JSON output of the service.

{
    "category": 
    {
        "domain": "ecommerce",
        "priority": 1
    },
    "metrics": 
    [
        {
            "KPI": 
            {
                "conversions":[
                    {
                        "channel": "social",
                        "quantity": 3
                    }
                ]
            }
        },
        {
            "rate": {
                "score":[
                    7.8
                ]
            }
        }
    ]
}

The path property for score in this response is metrics[1].rate.score[0].

10. Click Save to apply your changes.

Once you have saved the custom model, it will appear on the Custom models page.

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Item	Description
Name	Name of the custom model.
Type	Type of the custom model such as Single Upload or Bulk Upload.
Status	The status of the run command on the custom model.
Score	Indicates the score of the custom model.
Actions	Option to perform activities such as Edit, Delete, and Run.
Group by	View the items in a specific Group (For example, Name, Type, status, and score).
Run History	See the run history of the custom models.

To Run, Edit, and Delete the workflow

Follow the below step to perform actions for the custom models:

• On the Custom models page, select the horizontal ellipsis in the Actions column and do the following:

If you want to	Then
Edit a workflow for previously created custom model	Select Edit and modify the custom models. Click Save to apply your changes.
Remove a workflow	Select Delete and click Yes to remove the custom model.
Execute the custom model	Select Run.