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CS294A/CS294W
Deep Learning and Unsupervised Feature Learning
Winter 2011
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- To learn more about deep learning and unsupervised feature learning, please work through the tutorial at http://deeplearning.stanford.edu/wiki/.
- The first class will meet on Wednesday January 5th, 4.15-5.30pm, in Gates 120.
If you are unable to attend this but would like to
take CS294A, please (i) Email us at
cs294a-qa@cs.stanford.edu
to let us know, and (ii) Print out a hardcopy of the
class survey, fill it out, and drop off the hardcopy
in Prof. Ng's mailbox in Gates 143.
In this class, we will develop unsupervised deep learning algorithms that
are capable of learning useful features for a range of machine learning
applications. Unlike most previous CS294A's, this course will pursue
work in developing new machine learning algorithms
(i.e., "core" or "algorithmic" machine learning) rather than in "applied" machine
learning.
Because it is challenging to work on
algorithmic machine learning, we will be able to work with only a
small number of students, and enrollment will be limited.
You can find details about enrollment requirements
on the Handouts and enrollment information page.
Course Instructor:
Andrew Ng.
(ang@cs.stanford.edu)
Class meetings:
This is a project course. There will be no weekly lectures, and only two
introductory homeworks. We will spend the quarter working in teams on different
deep learning related projects.
The whole class will meet on 5th January (4.15pm-5.30pm, Gates 120)
and 9th Feb (4.15-5.30pm).
Final project presentations will be
held Thursday, March 17, 1:30pm-3:00pm.
If you were unable to attend the first meeting but would like
to take CS294A, please email
cs294a-qa@cs.stanford.edu
to let us know.
More information: