In this hands-on lab, you will become familiar with creating a batch inferencing pipeline and obtaining its outputs in Azure Machine Learning.
Successfully complete this lab by achieving the following learning objectives:
- Create a Compute Resource and Access the Provided Jupyter Notebook
Utilize the provisioned workspace to create a compute instance. This will be used to power a Jupyter notebook and execute your machine learning tasks.
If you plan to utilize the existing Jupyter notebook with the data and steps required to create and run the experiment already preconfigured, clone the repo from GitHub.
- Train and Register a Model
Train and register a model to use in your batch inferencing pipeline.
- Simulate Sample Data
Generate random data to simulate the thousands of patient records that are uploaded each day.
- Create and Run a Batch Inferencing Pipeline
Build the necessary steps to create a batch inferencing pipeline, and then execute it.
- View the Results
Obtain the outputs produced by the experiment.