Submission information
Submission Number: 204
Submission ID: 4061
Submission UUID: 3c8b9d7e-5b52-4f39-b22a-6fa56569b6cf
Submission URI: /form/resource
Created: Fri, 09/29/2023 - 11:48
Completed: Fri, 09/29/2023 - 11:48
Changed: Fri, 03/14/2025 - 11:43
Remote IP address: 18.29.105.203
Submitted by: Bao Nguyen
Language: English
Is draft: No
Webform: Knowledge Base Resources
Approved: Yes
Title: Machine Learning in Astrophysics
Category: Docs
Skill Level:
Intermediate (305)
Description:
Machine learning is becoming increasingly important in field with large data
such as astrophysics. AstroML is a Python module for machine learning and
data mining built on numpy, scipy, scikit-learn, matplotlib, and astropy
allowing for a range of statistical and machine learning routines to analyze
astronomical data in Python. In particular, it has loaders for many open
astronomical datasets with examples on how to visualize such complicated and
large datasets.
Link to Resource:
- Astroml webpage (https://www.astroml.org/)
- Examples (https://www.astroml.org/examples/index.html)
- Interactive notebooks (https://www.astroml.org/astroML-notebooks/)
Tags:
plotting (784), big-data (4), image-processing (299), machine-learning (272), astrophysics (297)
Domain:
ACCESS CSSN (780), Campus Champions (572), CAREERS (323), CCMNet (835), Great Plains (311), Kentucky (322), Northeast (308)
Would you like to associate this resource with an Affinity Group?: {Empty}