Track 06Build
3 modules · 2 labs

Experiment Tracking & MLflow

Log parameters, metrics, and artifacts across training runs, compare model performance, and register production-ready models.

Assumes: Data Science Foundations & Python scripting.

Modules

  1. The Experiment Tracking Problem in Data Science
  2. Logging Parameters, Metrics, and Artifacts with MLflow
  3. Model Registry Management & Versioning

Tools

  • MLflow
  • Python
  • Linux
  • Bash

Lab work

Linux scripting for automated experiment tracking, MLflow integration, and registry management.

 

View dashboard

Logging Parameters, Metrics, and Artifacts with MLflow