PHYS360  STATS, DATA MINING, MACH
This is a practical course on computing, numerical methods, statistics, and data analysis techniques with particular emphasis on data mining and machine learning applied to large datasets. Topics include basic numerical methods and algorithms, probability theory, classical and Bayesian statistical inference, model fitting, Monte Carlo methods, and classification. We will be using Python for the exercises. Prior experience in programming (in any language) is required.
Section 001  LEC
MW 0100PM0230PM
R 0400PM0500PM
R 0400PM0500PM
SAKO, MASAO
DAVID RITTENHOUSE LAB 3N1H
DAVID RITTENHOUSE LAB 3N1H
DAVID RITTENHOUSE LAB 3N1H
Events

Astro Seminar:"Probing Galaxy Formation with Modern Cosmological Simulations"
February 21, 2018  2:00 pm
Paul Torrey (MIT)
David Rittenhouse Laboratory, A4

Condensed Matter Seminar: "Enhanced optical and magnetic microscopy by orientationdependent modulation of singlemolecule and nitrogenvacancycenter emission"
February 21, 2018  4:00 pm
Mikael Backlund (Harvard University)
David Rittenhouse Laboratory, A4

High Energy Theory Seminar: (TBA)
February 26, 2018  2:00 pm
Rob Leigh (U of Illinois  Urbana Champaign)
David Rittenhouse Laboratory, 2N36