A regression model analyzes your tabular data and returns a numeric value. For example, you could train a model to estimate the value of a house.
A classification model analyzes your tabular data and returns a list of categories that describe the data. For example, you could train a model to predict whether the purchase history for a customer predicts that they will buy a subscription or not.
Workflow for creating a classification or regression model and making predictions
The process for creating a classification or regression model in Vertex AI is as follows:
| Steps | Description |
|---|---|
| 1. Prepare tabular training data | Prepare your tabular training data for model training. |
| 2. Create a dataset | Create a new dataset and associate your prepared training data to it. |
| 3. Train a model | Train a classification or regression model in Vertex AI using your dataset. |
| 4. Evaluate your model | Evaluate your newly trained model for prediction accuracy. |
| 5. Get predictions from your model | If you want real-time predictions, you can deploy your model and get online predictions. If you don't need real-time predictions, you can make batch predictions requests directly to your model. |