Hello. In this lesson, you will learn how to deploy batch inference pipelines
with Azure Machine Learning. In many production scenarios, long-running tasks that
operate on large volumes of data are performed
as batch operations. In Machine Learning, batch inferencing
is used to apply a predictive model to multiple
cases asynchronously, usually writing the results
to a file or database. In Azure Machine Learning, you can implement Batch
Inferencing solutions by creating a pipeline that includes a
step to read the input data, load a registered model, predict labels, and write
the results as its output. In this lesson, you will publish a batch inference pipeline
for a trained model, and use a batch
inference pipeline to generate predictions.