University of California at
Berkeley
Dept. of Electrical Engineering
& Computer Science
Dept. of Statistics
STAT 241A / EECS 281A
Statistical Machine Learning
Fall Semester 2016
Instructor:
Martin Wainwright
Announcements:
-
- The course website will be hosted on Piazza; details forthcoming
during the first week of lecture.
- The first lecture in this class will be on Tuesday, August 30, 2016
- NOTICE TO UNDERGRADUATES:
I have received an extremely large volume of emails from undergraduates, and do not have the bandwidth to reply to them all. Instead, please
read these instructions carefully.
This is a graduate class. Even if you have the technical
background to take it, you may not have the intellectual and mathematical
maturity. A graduate course presumes
that students are independently motivated,
and take initiative to teach themselves what they do not know.
With this mind, undergraduates will be allowed to enroll
in this class only with special permission from the instructor.
Given the huge number of undergraduates expressing interest in this class,
there will definitely not be enough spaces for all who are
interested and qualified.
To assess qualifications, there will
be an entrance examination for the undergraduates, held during the first week class. Based on performance on this examination, a very small number of
undergraduates may be admitted.
The examination will assess whether you have the required background in probability (at the level of EECS 126) and linear algebra (at the level of MATH
110), along with some degree of mathematical maturity. Unless (at a bare
minimum) you have taken these classes and received A or higher grades, this
class is probably not suitable for you.
-
UNDERGRADUATE TAKE-HOME EXAM:
The download link below will be
active
by 3:30 pm on
Thursday, September 1st. Must be handed in (HARD COPY only) to the
EECS front office in Cory Hall, 2nd floor, no later than 3:30pm on
Friday, September 2nd. There will be a box here for you to turn in
your completed exams. NO LATE EXAMS accepted.
Download the exam