Interactive Machine Learning is an exciting topic within the fields of Artificial Intelligence, Automation, and Big Data and Smart Data. It is a method where humans and machines work closely together to develop learning algorithms. Unlike classic machine learning, where the computer mostly analyses large amounts of data on its own, the interactive approach specifically involves experts or users. They provide feedback to the machine so that it achieves better results.
Imagine a company wants to improve its email filters to automatically detect unwanted messages. With interactive machine learning, an employee regularly flags irritating or desired emails. Each piece of feedback helps the system learn to distinguish between „spam“ and „important“ better and better. This makes the filter more practical for everyday use and also better prepared for new, unknown messages.
By involving people, errors can be identified and corrected more quickly. Companies benefit from this because they get more efficient, flexible systems that incorporate human experience and judgment. Interactive Machine Learning thus makes Artificial Intelligence more understandable, familiar, and adaptable.
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