Training vs Inference
/ˈtreɪnɪŋ vɜːsəs ˈɪnfərəns/
Definition
Training updates model weights using data; inference applies a fixed model to new inputs to make predictions.
Example in context
"Training runs on 8 GPUs overnight — inference needs only one GPU and must respond in under 100ms."
Related terms
Practice this term
Master Training vs Inference in context by working through exercises in the Data Science & ML module. You'll see the term used in real engineering scenarios with multiple-choice, fill-in-the-blank, and matching drills.