Offline Learning

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What Does Offline Learning Mean?

In the machine learning world, offline learning refers to situations where the program is not operating and taking in new information in real time. Instead, it has a static set of input data. The opposite is online learning, where the machine learning program is working in real time on data that comes in.

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Techopedia Explains Offline Learning

Offline learning is sometimes described as a proactive type of learning that can work forward on the basis of evaluating the static data sets that it has at its disposal. Because there is no continual influx of information, the program and its human operators can benchmark the results of the training set and apply them to future phases of operation. Some experts call offline learning a form of eager learning, which means that the system is working proactively to make decisions, as compared to lazy learning where the machine learning program's work may be event driven.

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Margaret Rouse
Technology Expert
Margaret Rouse
Technology Expert

Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.