"When modeling a system, it should be as minimally detailed as required to be maximally useful for its intended purpose."

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"When modeling a system, it should be as minimally detailed as required to be maximally useful for its intended purpose."

medium.com

aebrer@kbin.social to

Machine Learning@kbin.social · 1 year ago

When Is A.I. Trustworthy? When Is A.I. Useful?

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What a map to a Garfield-themed restaurant can teach us about A.I.

This is an article I wrote in 2019 about modeling and entropy. It’s something I consider daily as I work on modeling in the drug discovery space.

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Machine Learning@kbin.social

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Machine learning (ML) is a field devoted to understanding and building methods that let machines “learn” – that is, methods that leverage data to improve computer performance on some set of tasks. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

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