Automatically track XGBoost training progress to Neptune

  • Log XGBoost metrics to Neptune (train and eval)
  • Log model, feature importance and trees visualizations for deeper analysis
  • Compare across multiple experiments
Experiments tracking
Experiments sharing in the team
Experiments comparison
Notebooks tracking and sharing
Notebooks comparison
Team management
Open source integrations
Hardware monitoring for experiments
Interactive experiments dashboard

XGBoost metrics logged to Neptune automatically

Experiment tracking tool with XGBoost integration, to automatically log training and validation progress.

Develop XGBoost train or cv functions in a regular way. If you prefer the sklearn API it’s fine too. Then, simply add neptune_callback that will log metrics, model, feature importance charts and visualized trees out-of-the-box.

Easy logging

  • Log metrics, text, images, files and more to the experiments.
  • Log experiment parameters.
  • Easy integration with Python libraries.

Shareable visualizations

  • All charts visible for team members.
  • Compare across multiple experiments and gain insight.
  • Download charts from UI.

Backed up experiments history

  • All visualizations are stored and secured.
  • Keep all history – review when needed.
  • Secured Intellectual Property (IP).

Register and try it out!