Navigating the H2O Hydrogen Torch Interface
- Predictive AI
- H2O Hydrogen Torch
This lesson orients new users inside H2O Hydrogen Torch's interface, starting from the home page where datasets and experiments are listed side by side. It walks through the left navigation menu section by section: Settings for appearance and default experiment configuration, Documentation for in-depth guidance, Datasets for importing data from sources like AWS S3, Azure Data Lake, or Kaggle, and Experiments for creating and tracking runs with options like grid search. It closes by covering the Projects section for organizing related experiments and the Predictions tab for scoring new data once a model has been trained.
Key takeaways
- How the Datasets and Experiments lists on the Hydrogen Torch home page summarize what's available at a glance
- What sources a new dataset can be imported from, including AWS S3, Azure Data Lake, Kaggle, or a direct upload
- What the grid search option on the Experiments page lets you do when creating a new run
- How the Projects section helps organize experiments once more than one is in progress
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