This course is an introduction to the core concepts in machine
learning with an emphasis on applications in physical sciences, including
quantum physics, statistical mechanics, and quantum information processing.
Lectures will cover the basic theory underlying several modern areas of machine
learning and have practical components wherein applied techniques in machine
learning are discussed. Students are expected to be comfortable with
programming in Python 3.
Develop a basic understanding of
learning algorithms and their areas of application; |
Get acquainted with practical
ingredients of machine learning projects; |
Develop required skillset for
performing a team-wide software project; |
Get involved in reading and
understanding machine learning literature; |
Develop the skillsets required for
reproducing the results reported in machine learning literature. |
Additional topics, time allowing:
Programming resources
Title / Name |
Notes / Comments |
Required |
A computing platform for programming |
E.g. a laptop. |
Yes |
A Github
account |
The free account is sufficient (http://www.github.com/) |
Yes |
More resources
Title / Name |
Notes / Comments |
Required |
Deep Learning by I Goodfellow, Y Bengio, and A Courville |
No |
|
Stanford CS 229 notes |
No |
|
UBC CPSC 540 notes |
No |
|
Applying machine learning to physics |
No |
All assignments and the final project are done through Github. The student is required to make an account on Github and provide the account ID to the instructor/TA of
the course.
Deep Learning (Goodfellow, Bengio,
Courville) is perhaps as close as a textbook can get to overlap the topics of
this course. Yet many topics discussed here will be skipped and several topics
of our focus are out of the content of this book. Similar to other ML
textbooks, this book comes in hundreds of pages, so perhaps an introductory
short read to general topics in ML are The Hundred-Page Machine Learning Book
(by Andriy Burkov) and Neural Networks and Deep
Learning (by Michael Nielsen). None of these books are required material for
the course.
For some more advanced topics refer to Stanford CS 229 and UBC
CPSC 540. We will touch some of the material discussed in these courses as they
are relevant to applications in physics.