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About Dalya Baron: Draft Version April 17, 2019 Typeset Using L Tex Preprint2 Style in Aastex61
This document provides an overview of machine learning techniques that are increasingly being used in astronomy. It summarizes topics presented at the 2018 IAC Winter School, including supervised and unsupervised machine learning algorithms. Supervised learning involves using labeled example data to learn a mapping from features to a target variable. Popular supervised algorithms discussed are support vector machines, random forests, and neural networks. Unsupervised learning techniques like clustering, dimensionality reduction, and anomaly detection can extract new knowledge from datasets without labels. The document aims to give astronomers practical information on applying these algorithms to analyze large astronomical datasets.
Detailed Information
| Author: | ['Aga Matha'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 37 |
| Language: | English |
| Format: | |
| Price: | FREE |
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