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
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!
library(neptune) 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_artifact('model.Rdata') ... # 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.
- 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!