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

Astronomy seminar: "The Hunt for Exomoons"
October 24, 2018  2:00 pm
David Kipping, Columbia University
David Rittenhouse Laboratory, A6

Condensed Matter Seminar: "Taming Quantum Entanglement"
October 24, 2018  4:00 pm
Matthew Fisher, University of California, Santa Barbara
David Rittenhouse Laboratory, A6

Experimental Particle Physics Seminar: "Recent results from T2K"
October 24, 2018  4:00 pm
Alysia Marino, University of Colorado
David Rittenhouse Laboratory, 2C2