You can drag-and-drop datasets and modules onto the canvas.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

Explanation

To perform real-time inferencing, you must deploy a pipeline as a real-time endpoint.
Real-time endpoints must be deployed to an Azure Kubernetes Service cluster.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer#deploy

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/chit-chat-knowledge-base?tabs=v1

Explanation

Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-service-manage-channels?view=azure-bot-service-4.0

Section: Describe Artificial Intelligence workloads and considerations
Explanation:
In Azure Machine Learning, the percentage split is the available technique to split the data. In this technique, random data of a given percentage will be split to train and test data.
Reference:
https://www.sqlshack.com/prediction-in-azure-machine-learning/