[4eyes] FW: [FACULTY] FYI: grad course "statistics, data analysis, and machine learning for physicists."

[Matthew Turk]

FYI

 

From: faculty [mailto:faculty-bounces at lists.cs.ucsb.edu] On Behalf Of Wim Van Dam
Sent: Monday, March 5, 2018 12:11 PM
To: faculty at cs.ucsb.edu
Subject: [FACULTY] FYI: grad course "statistics, data analysis, and machine learning for physicists."

 

Dear all, 

 

See below for the announcement of a spring graduate course in the physics department on "Statistics, data analysis, and machine learning for physicists". Maybe that some of our students are interested in this as well. 

 

Wim 

 

 

---------- Forwarded message ----------
From: Timothy Brandt <tbrandt at physics.ucsb.edu <mailto:tbrandt at physics.ucsb.edu> >
Date: Fri, Mar 2, 2018 at 1:02 PM
Subject: Special topics class--please forward to potentially interested grad students



Dear faculty,

 

I will be teaching a special topics course this spring on statistics, data analysis, and machine learning for physicists.  The class will meet MW from 12:30-1:45.  I expect to assign a problem set every 1-2 weeks along with a somewhat open-ended final project.  I will use the following textbooks:

Statistics, Data Mining, and Machine Learning in Astronomy

Numerical Recipes: The Art of Scientific Computing

While the first textbook has the word "astronomy" in the title, I hope to make the course of more general interest than this and to include examples from, at the least, high-energy experiments.  My goal is to introduce statistical concepts and their applications to data, covering common methods and where they are and are not appropriate.  In short, I want students to be able to make sense of their own data, and to critically interpret the data analysis sections of papers that they read.  I'll also briefly touch on machine learning, which is the latest buzzword.  Forms of machine learning (neural networks, deep learning, etc.) are present in a lot of paper titles, at least in astrophysics, and I suspect in biological physics, too.  This buzzword covers a wide range of techniques and I will introduce at least some of the more basic, established, and useful ones.

 

Please forward this information to any of your graduate students who may be interested, and please also forward it to faculty you know in related departments.  Any of them are free to contact me if they want more details.

 

Thanks very much,

 

Tim Brandt

 

 

 

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