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Tutorial 1A: Introduction to H2O Driverless AI

Introduction​

Overview​

This tutorial is a quick start of H2O Driverless AI (DAI) and gives you a quick overview of the high-level capabilities and use cases you can achieve using H2O Driverless AI.

We will explore the Titanic dataset from the perspective of a passenger life insurance company and analyze the possible risk factors derived from this dataset that could have been considered when selling passenger insurances. More specifically, we will create a predictive model to determine what factors contributed to a passenger surviving.

Objectives​

In this tutorial, you will get hands-on experience covering the following basic functions of H2O Driverless AI:

  • Data loading
  • Generating autovisualizations
  • Setting up an experiment
  • Explore feature engineering
  • Result interpretation

Prerequisites​

  • Access to Lab 23 in Aquarium containing H2O Driverless AI v1.10.7 (LTS)
    note

    To learn how to access Lab 23 in Aquarium, see Access an Aquarium lab.

Once you are all set up on Aquarium, proceed to Task 1 of this tutorial to begin.

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