Finding structures in astronomical data with machine learning
Title
Finding structures in astronomical data with machine learning
Subject
Physics
Description
Astronomy is experiencing a rapid growth in complexity and data size. The difficulty in analysing data
fosters the development of data-driven science as a useful companion where astronomers develop tools
to mine datasets and extract novel information from them. In recent years, machine learning algorithms
have been popular risen among astronomers, and are now used for a wide variety of tasks.
fosters the development of data-driven science as a useful companion where astronomers develop tools
to mine datasets and extract novel information from them. In recent years, machine learning algorithms
have been popular risen among astronomers, and are now used for a wide variety of tasks.
Creator
Wanying Zhao
Date
2022
Abstract
Astronomy is experiencing a rapid growth in complexity and data size. The difficulty in analysing data
fosters the development of data-driven science as a useful companion where astronomers develop tools
to mine datasets and extract novel information from them. In recent years, machine learning algorithms
have been popular risen among astronomers, and are now used for a wide variety of tasks.
fosters the development of data-driven science as a useful companion where astronomers develop tools
to mine datasets and extract novel information from them. In recent years, machine learning algorithms
have been popular risen among astronomers, and are now used for a wide variety of tasks.
Files
Collection
Citation
Wanying Zhao, “Finding structures in astronomical data with machine learning,” URSS Showcase, accessed May 8, 2024, https://urss.warwick.ac.uk/items/show/305.