Explore best practices for DP-100: Designing and implementing a data science solution on Azure learning path 6
DP-100: Learning Path 6 Track model training in Jupyter notebooks with MLflow
Learning Path 6 Overview
As you begin to teach this learning path, get familiar with what the students will learn during the learning path. In this learning path students will learn about tracking model training in Jupyter notebooks with MLflow and how to use MLflow for tracking models and experimenting in Jupyter notebooks.
This learning path consists of four focus areas:
- Mlflow overview
- Configure and use Mlflow in notebooks
- Track model training in notebooks with MLflow
- Mlflow logging methods
Learning Path 6 Tips and Tricks
- Describe a Mlflow solution overview with a good architecture diagram
- Revisit the full iterative process to show model choice process in more details
- Provide a code walk-through for classes, objects, and methods necessary
Learning Path 6 Demos (optional)
- Discuss the experiment
- Logging an artifact and revisiting it in Azure Machine Learning UI
Learning Path 6 Lab