Inference

What is Inference?

When developing a machine learning model, there are two main phases:

1. Training
2. Inference

Take the example of classifying spam emails. Once the model has been trained, new emails can be fed into the model to make a prediction as to whether the email is spam or not. In the Inference stage, the model isn’t learning or updating its parameters. It’s just making predictions based on the patterns it has learnt to recognise in the data from the Training stage. During this stage, the data is input to the trained model and a predicted label is output.

Related Terms

• Training