Astronomers from NASA's Jet Propulsion Laboratory in Pasadena, California, are turning to "machine learning" to help them sort and identify basic properties of thousands of stars in our galaxy.

Machine learning is a discipline that uses algorithms capable of learning from data input. It's being used in many fields and can predict what users want to watch on TV, for example.

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"It's like video-streaming services not only predicting what you would like to watch in the future, but also your current age, based on your viewing preferences," said Adam Miller of NASA's Jet Propulsion Laboratory.

"We are predicting fundamental properties of the stars," Miller added.

Astronomers will use this technique to collect information on billions of stars in a short amount of time. The technique is also less expensive.

"We can discover and classify new types of stars without the need for spectra, which are expensive and time-consuming to obtain," said Miller.

It isn't the first time machine learning will be applied to studying the cosmos, but it's the first to predict specific traits of stars, such as size and metal content.

These traits will help astronomers understand the birth of stars and their changes since their beginnings.

"With more information about the different kinds of stars in our Milky Way galaxy, we can better map the galaxy's structure and history," said Miller

TagsNASA, Jet Propulsion Laboratory, california, Pasadena, Machine Learning, Stars, Galaxy, Cosmos