Program Overview

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Physics 568: LARGE SCALE DATA ANALYSIS IN PHYSICS & ASTRONOMY, SPRING 2023

Instructor Information

The instructor for this course is Prof. Alexandre V. Morozov, with office hours by request.

Lectures

Lectures are held on Tuesdays and Fridays from 10:20 am to 11:40 am in SEC-204.

Textbooks

The required textbooks for this course are:

• Pattern Recognition and Machine Learning (Information Science and Statistics) by Christopher M. Bishop
• Information Theory, Inference and Learning Algorithms by David J. C. MacKay

Reviews

Recommended review material includes:

• Introduction to Machine Learning for physicists by Pankaj Mehta et al.

Prerequisites

The prerequisites for this course are basic knowledge of linear algebra and probability theory.

Homework and Exam

• One homework assignment is given every 2-3 weeks.
• There will be a final take-home project (72 hours, open book, open notes).

Grading

The grade is determined according to the following formula: total score = 1/2(homework) + 1/2(final)

Lecture Notes

Lecture notes are available for the following dates:

• Lecture 1 (01/17)
• Lecture 2 (01/20)
• Lecture 3 (01/24)
• Lecture 4 (01/27)
• Lecture 5 (01/31 and 02/03)
• Lecture 6 (02/07)
• Lecture 7 (02/10)
• Lecture 8 (02/14)
• Lecture 9 (02/17)
• Lecture 10 (02/21)
• Lecture 11 (02/24)
• Lecture 12 (02/28 and 03/03)
• Lecture 13 (03/07 and 03/10)
• Lecture 14 (03/21)
• Lecture 14 Supplement
• Lecture 15 (03/24 and 03/28)
• Lecture 16 (03/31)
• Lecture 17 (04/04)
• Lecture 18 (04/07)
• Lecture 19 (04/18)
• Lecture 20 (04/21)
• Lecture 21 (04/25)
• Lecture 22 (04/28)

Homework

Homework assignments are due on the following dates:

• Homework 1 (due 02/10)
• Homework 2 (due 03/03)
• Homework 3 (due 03/31)
• Homework 4 (due 04/28)

Final Exam

The final exam is due on 05/05 by 5 pm.

Notes

• There is no lecture on Friday, Feb. 17.
• There are no lectures on Tuesday, Apr. 11 and Friday, Apr. 14 due to a strike.

Accommodations

Students with disabilities should be accommodated according to university policies.