MLFlow in Action: Hands on guide to ML experiments
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Section 1: Getting Started
- Need for MLFlow
- Download Resources
- Installation
Section 2: MLFlow Tracking
- Experiment vs Run
- Demo of typical Data Science Project (Sklearn Experiment)
- MLFlow Tracking Steps
Section 3: Understanding MLruns Directory
- Components of MLruns directory (Understanding MLruns Directory)
- Tracking UI
- Model Registry
Section 4: Advanced Functionalities
- Changing tracking Location
- Multiple Runs and Experiments (Launch multiple runs)
- Autologging
- Tracking server