Chapter 8: Experimenting with Python Code

In this chapter, you will understand how to train Machine Learning (ML) models with code. You will start with a simple ML model using the Python scikit-learn library, which is commonly referred to as sklearn. You will understand how you can keep track of the training metrics using the Azure Machine Learning (AzureML) SDK and MLflow. Then, you will see how you can scale out the training process in compute clusters.

In this chapter, we are going to cover the following topics:

• Training a simple sklearn model within notebooks
• Tracking metrics in Experiments
• Scaling the training process with compute clusters