Deploy your trained machine learning model to start generating predictions
In this article, you will deploy your trained machine learning model. Your deployed model will be hosted on PI.EXCHANGE's cloud, and can remain active 24/7 to receive requests and generate predictions.
1. Select Deployments
Select DEPLOYMENTS in the left navigation, and click on DEPLOY MODEL.
Step 1: Select a Model
- Model: Select the XGBoost Classifier model that had the better performance.
- Trained on dataset version: Ignore as this relates to Continuous Learning.
- Automatically deploy updated versions of the same model: Leave it switched off as it relates to Continuous Learning.
Step 2: Choose deployment
- Select DEPLOY TO PI.EXCHANGE CLOUD
- Deployment Name: XGBoost Classifier
- Deployment Description: Optional
Step 3: Choose deployment target
- Select DEPLOY TO NEW ENDPOINT
- Endpoint Name: Predict Delinquency
- Endpoint Description: Optional
Note: An endpoint is like a URL assigned to your deployment, which is where your prediction request should send to. For more information, see How to assign and reassign deployments to an endpoint?
Congratulations, you have successfully trained and deployed your very own machine learning model!