Use the Google Cloud Console to train an AutoML image classification model. After your dataset is created and data is imported, use the Cloud Console to review the training images and begin model training.
This tutorial has several pages:
Training an AutoML image classification model.
Each page assumes that you have already performed the instructions from the previous pages of the tutorial.
1. Review imported images
After dataset import you will be taken to the Browse tab. You can also access this tab by selecting Datasets from the side menu, then selecting the annotation set (set of single-label image annotations) associated with your new dataset.
2. Begin AutoML model training
In the Browse tab you can choose Train new model to begin training. You can also start training by selecting Models from the side menu, then selecting Create.
Select Create to open the Train new model window.
In the first "Choose training method" section choose the target Dataset and Annotation set if they are not automatically selected. Make sure theAutoML radio button is selected, and then choose Continue.
In the following "Define your model" section, fill the Model name field (optional), and then choose Continue.
In the final "Compute and pricing" specify a node hour budget of 8 node hours, and select Start training.
Training takes several hours. You will receive a notification email when model training finishes.
Follow the next page of this tutorial to deploy your trained AutoML model to an endpoint and sent an image to the model for prediction.