ASTR 324, Spring 2020, University of Washington:

Introduction to Statistics and Machine Learning in Astronomy

Mario Jurić, @mjuric on GitHub

This repository ASTR 324 class materials. To get the latest versions into the class JupyterHub, make sure you're logged in and then click:

https://tinyurl.com/astr324-s20-refresh-nb

Location

• When: TTh, 10:00am-11:20pm
• Where: http://ls.st/324

Class Materials

• Syllabus and course description
• Lectures: Notebooks, Videos
• Canvas (used for quizzes only).
• Homework assignments
• JupyterHub: JupyterHub, instructions

Reference textbook

Ivezić, Connolly, VanderPlas & Gray: Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data; first or second edition.

Class Description

This course introduces students to statistical and computer science tools and techniques commonly used in data driven astronomy and astrophysics. It does so through a hands-on approach, with theory followed by working through examples of data analysis with modern astronomical datasets. Practical data analysis is done using Python tools, with emphasis on the astroML module (see www.astroML.org). The lectures taught at the undergraduate level, designed for astronomy and physics majors. The main discussion topics are based on Chapters 4 and 5, and selected topics from Chapters 6-10, from the reference textbook.