juniorMLOps
What is experiment tracking in ML?
Updated May 17, 2026
Short answer
Experiment tracking records parameters, metrics, and outputs of ML experiments.
Deep explanation
It ensures reproducibility and comparison across multiple model runs. Tools like MLflow log hyperparameters and results.
Real-world example
Comparing multiple deep learning models for image classification.
Common mistakes
- Not logging all hyperparameters.
Follow-up questions
- Why is tracking important?
- What tools are used?