Exam DP-100 topic 4 question 49 discussion

answer should be 1.Create and run training pipeline 2.Create and run a real-time inference pipeline 3.Deploy a serivce to an inference cluster https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-deploy

Create and run a training pipeline. This is the first step because before you can create a prediction model, you need to train it with existing data. This is done by creating and running a training pipeline, which takes in your data, applies a machine learning algorithm, and outputs a model that can be used to make predictions. Create and run a real-time inference pipeline. Once the model has been trained, it's time to use it for prediction. This is done by creating a real-time inference pipeline. The inference pipeline takes in new data, applies the trained model, and outputs predictions. Deploy a service to an inference cluster. After you have a working inference pipeline, you can deploy it as a web service to an inference cluster. This allows applications to send data to the service and receive predictions in return. This is the last step because you need a trained model and a working inference pipeline before you can deploy a service.