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Offline inference: Difference between revisions
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(Created page with "{{see also|Machine learning terms}} ==Offline Inference in Machine Learning== Offline inference, also known as batch inference, is a process in machine learning whereby a trained model is used to make predictions on a dataset in a non-interactive or non-real-time manner. This approach allows for the efficient processing of large datasets, as it does not require an immediate response to user inputs. ===Characteristics of Offline Inference=== Offline inference is char...") |
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* '''Periodic updates:''' In some cases, offline inference may be used to periodically update a system's state based on new data, such as updating recommendations in a [[recommender system]]. | * '''Periodic updates:''' In some cases, offline inference may be used to periodically update a system's state based on new data, such as updating recommendations in a [[recommender system]]. | ||
==Explain Like I'm 5 (ELI5)== | |||
Imagine you have a robot that can predict what type of ice cream people will like. With offline inference, you give the robot a list of people and the robot thinks about it for a while before giving you a list of ice cream predictions for everyone. It doesn't need to tell you right away what each person likes, and it doesn't need you to keep giving it more information while it's thinking. The robot can take its time to process everything and give you the best possible answers. | |||
==Explain Like I'm 5 (ELI5)== | ==Explain Like I'm 5 (ELI5)== | ||