Tutorials

This section contains detailed walkthroughs for specific use cases.

•  Tracking experiments

  ---

  • Track and organize model training runs
  • Monitor model training live
  • Visualize cross-validation results
  • Track hyperparameter tuning (HPO) runs

•  Reproducibility

  ---

  • Reproduce a run
  • Restart a run from a saved checkpoint
  • Rerun a failed training

•  Data versioning

  ---

  This set of tutorials covers artifact version tracking and comparison.

  • Version datasets in runs
  • Compare datasets between runs
  • Share dataset versions on project level

•  Advanced

  ---

  • Track distributed training jobs
  • Log in a sequential pipeline
  • Track models end-to-end

---

The related Colab notebooks and all necessary scripts are located in our GitHub examples repository.

Visit examples repo