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:
|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.