Hello text data

This tutorial walks you through the required steps to train and get predictions from your text classification model in the Google Cloud console.

In this tutorial, you'll train an AutoML model by using a collection of crowd-sourced "happy moments" from the Kaggle open source dataset HappyDB. The resulting model classifies happy moments into categories reflecting the causes of happiness.

To complete this tutorial, you can either follow the instructions in the following pages or use the in-console walkthrough tutorial, which is a similar tutorial in the Google Cloud console.

Tutorial pages

This tutorial has several pages:

  1. Setting up your project.
  2. Creating a text classification dataset.
  3. Training an AutoML text classification model.
  4. Deploying the model for batch predictions.
  5. Cleaning up your project.

In-console walkthrough tutorial

These two tutorials are available in the Google Cloud console.

Part 1

In Part 1 of the in-console walkthrough tutorial, you'll learn how to build a text classification model using Google's AutoML technology.

To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me:

Guide me

Part 2

This is the second tutorial on building an AutoML text classification model. You'll need the model you trained in Part 1 to continue.

  • Follow up tutorial (optional)

    To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me:

    Guide me

Next
Set up your project and environment