Forecasting models predict a sequence of values. For example, as a retailer, you might want to forecast daily demand of your products for the next 3 months so that you can appropriately stock product inventories in advance.
Workflow for creating a forecast model and making inferences
The process for creating a forecast model in Vertex AI is as follows:
| Steps | Description |
|---|---|
| 1. Prepare tabular training data for forecast models | Prepare your tabular training data for forecast model training. |
| 2. Create a dataset for training forecast models | Create a new dataset and associate your prepared training data with it. |
| 3. Train a forecast model | Train a forecast model in Vertex AI using your dataset. |
| 4. Evaluate your model | Evaluate your newly trained forecast model for inference accuracy. |
| 5. Get inferences for a forecast model | Request batch inferences from your forecast model. |
Forecasting with AutoML doesn't support online inferences. If you want to request online inferences from your forecast model, use Tabular Workflow for Forecasting.