Track machine learning experiments from R to Neptune

  • Log metrics, hyperparameters, charts, models and more to Neptune
  • Analyze machine learning experiments and share them with your team
  • Compare experiments and gain insights
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

Track machine learning experiments that you run in R to Neptune

Experiment management tool with R integration. Track machine learning model training to Neptune.

Neptune integration with R is available as a CRAN package. To track machine learning experiments to Neptune simply:

  • Import the package
  • Initialize Neptune and start your experiment 
  • log metrics, models, charts and organize your runs with names and tags

Everything will be automatically visible in the UI ready to be analyzed and shared with your team!

    init_neptune(project_name = 'shared/r-integration', api_token = 'ANONYMOUS')
    # Start an experiment and track hyperparameters
    create_experiment(name='training on Sonar',
                                   params = list( tuneLength=100,model="rf"))

    # track data version
    set_property(property = 'data-version', value = digest(dataset))
    # Log metrics
    log_metric('Train Accuracy', scores$TrainAccuracy)
    # Log artifact
    # Log image
    log_image('parameter_search', 'param_plot.jpeg')

Support for deep learning libraries

  • Start instantly with out-of-the-box integration.
  • Track rich data (metrics, text, images, files and more).
  • Save model weights.

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!