Which Machine Learning Course to take?
CIS 419/519 APPLIED MACHINE LEARNING
MW noon-1:30
Prerequisites: basic programming
Prof. Eric Eaton: eeaton@seas.upenn.edu or Dan Roth
http://www.seas.upenn.edu/~cis519/
CIS 519 is an introduction to machine learning (ML)
with an emphasis on applying ML techniques. It meets together with
an undergraduate version the same course (CIS 419), which has
somewhat different homework and project requirements. CIS 419/519
are intended for students who are interested in the practical application
of existing machine learning methods to real problems, rather than in
the statistical foundations of ML covered in CIS 520. The course will use
python.
CIS 520 MACHINE LEARNING
MW 10:30-noon and F 9:30-11:00 (the required recitation)
Prerequisites: linear algebra, probability basic programming
Prof. Lyle Ungar: ungar@cis.upenn.edu or Shivani Agarwal
https://alliance.seas.upenn.edu/~cis520/wiki/
CIS 520 is a more mathematically rigorous course in statistical
machine learning (ML) that provides the background necessary to
design and use new ML algorithms. It requires a basic knowledge of
linear algebra (matrices, eigenvectors, etc.) and probability and is said to require
a lot of work. Students planning on doing ML research or taking the
ML WPE exam should take this course.
CIS 519 is NOT a prerequisite for CIS 520.