Instructor: Dr. Tom Carter
DBH-287 667-3175
email: tcarter@csustan.edu
home page: https://csustan.csustan.edu/~tom
Texts: There is one required text and one suggested text for this course:
Required: Deep Learning with Python, 2nd Edition
by Francois Chollet
(ISBN-13: 978-1617296864)
(May be available online through the library)
Suggested: Computational Neuroscience - a First Course
by Hanspeter A. Mallot
(ISBN-13: 978-3-319-00860-8)
(I believe there is a copy in the library)
We'll talk about other resources for the course during the semester in class . . .
The plan is for us to meet at 11:00 a.m. on Tuesdays and Thursdays. For those who can meet in person, we will be meeting in DBH 100. For those who cannot meet in person, my plan is to have Zoom available. My Zoom ID is 2096673175 . Also, for those who cannot work synchronously at 11:00 a.m., I also expect to record class sessions, and make the recordings available through Canvas (Panopto Recordings). Thus, the plan is for this course to be available in person, synchronously through Zoom, and asynchronously through Canvas (with recorded class sessions). Each student may choose their own modality for the course, and may change modalities as their own circumstances may change.
Be sure to look at Discussions and Assignments.
Objectives:
A long-standing hope has been that computers will develop into intelligent assistants for us. Traditional approaches to computing (under the general description of von Neumann machines) have not led to particularly successful implementations of ``intelligent behavior.'' In recent years, several new approaches to computing have shown strong potential. In general, these approaches attempt to learn from the biological world which has led to human intelligence, and to apply abstractions from the biological world to the artificial world of computers.
Our primary focus will be on neural network approaches to computing, but we will also spend some time on other topics such as genetic algorithms and ``artificial life.'' The lab component of the course will involve hands on work with existing implementations of the various approaches to biologically inspired computing, or development of a new project, or research into other possible approaches.
The texts take a relatively mathematical approach to the topic, so be prepared -- but as usual, I will work to make the material comprehensible to all of us ...
Topics:
Grading:
The grades for this course will be based on three components: written responses to readings and brief exercises, a midterm exercise, and project(s). My expectation is that some of the projects will be developed by teams.
Each week, I want you to submit on Canvas (look in the "Assignments" section) a brief response to the readings for the week. We'll discuss this more as we move forward in the semester.
The components will be weighted approximately equally.
The work you do for this course will be your own. You are not to submit other people's or machine's work and represent it as your own. However, I do expect and encourage you to work collaboratively with others during the course.
Note that there is information about the University, policies, support services, accommodations, etc., in the University Catalog:
https://catalog.csustan.eduLinks to an external site.
In particular, information about student support services can be found here:
https://www.csustan.edu/student-servicesLinks to an external site.
Note also that it is possible there may be changes to the syllabus at any time, and that any changes to the syllabus will be communicated in a timely and transparent manner.