This tutorial walks you through the required steps to train and get predictions from your image classification model in the Google Cloud console.
This tutorial is part of the "Hello custom training" tutorial, which walks you through using Vertex AI to train an image classification model and serve predictions using the model. In this tutorial, you use Vertex AI's custom training feature to run a TensorFlow Keras training application in one of Vertex AI's prebuilt container environments. This custom training job trains a machine learning (ML) model to classify images of flowers by their type. After you train the ML model, the tutorial shows you how to create an endpoint and serve predictions from that endpoint to a web app.
Tutorial pages
This tutorial has several pages:
- Setting up your project and environment.
- Training a custom image classification model.
- Serving predictions from a custom image classification mode.
- Cleaning up your project.
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.
In-console walkthrough tutorial
In this tutorial, you'll learn how to build a multi-label image classification model using Google's AutoML technology. This tutorial is available in the Google Cloud console.
To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me: