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1.8.1

Release Notes

  • H2O Driverless AI Release Notes

Overview

  • Why Driverless AI?
  • Key Features
  • Supported Algorithms
  • Driverless AI Workflow

Installation, Upgrade, and Config

  • Installing and Upgrading Driverless AI
  • Using the config.toml File
  • Environment Variables and Configuration Options
  • Enabling Data Connectors
  • Configuring Authentication
  • Enabling Notifications

Using Driverless AI

  • Launching Driverless AI
  • The Datasets Page
  • Experiments
  • Diagnosing a Model
  • Project Workspace

Machine Learning Interpretability

  • MLI Overview
  • The Interpreted Models Page
  • MLI for Regular (Non-Time-Series) Experiments
  • MLI for Time-Series Experiments

Scoring on New Datasets

  • Score on Another Dataset

Transforming Datasets

  • Transform Another Dataset

Scoring Pipelines

  • Scoring Pipelines Overview
  • Visualizing the Scoring Pipeline
  • Which Pipeline Should I Use?
  • Driverless AI Standalone Python Scoring Pipeline
  • Driverless AI MLI Standalone Python Scoring Package
  • MOJO Scoring Pipelines

MOJO Pipeline Deployments

  • Deploying the MOJO Pipeline

What's Happening?

  • What’s Happening in Driverless AI?
  • Data Sampling
  • Driverless AI Transformations
  • Internal Validation Technique
  • Missing and Unseen Levels Handling
  • Time Series in Driverless AI
  • NLP in Driverless AI

Python and R Clients

  • The Python Client
  • The R Client

Logs

  • Driverless AI Logs

Security

  • Driverless AI Security

Frequently Asked Questions

  • FAQ
  • Tips ‘n Tricks

Appendices

  • Appendix A: Custom Recipes
  • Appendix B: Third-Party Integrations

References

  • References
Using Driverless AI
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