Definition
Model inference is the process of using a trained machine learning model to make predictions on new, unseen data. It is generally less computationally intensive than model training.
Why it matters (in Poovi’s context)
Distinguished from model training, as the video clarifies that testing model training on a laptop is more intensive than inference, guiding hardware recommendations.
Key properties or components
- Prediction on new data
- Post-training phase
- Computational efficiency
Contradictions or debates
None.