ELEC 301 - Signals, Systems, and Learning - Fall 2016
This course deals with signals, systems, and transforms, from their theoretical mathematical foundations to practical implementation in circuits and computer algorithms to learning algorithms that convert signals into inferences.
The first half of the course follows the classical "physics" based approach, while the second half follows the more modern "machine learning" approach. In both halves, linear algebra plays a starring role. Fundamentally important, ELEC 301 acts as a bridge between the introductory ELEC 241/2 and more advanced courses such as ELEC 302, 303, 430, 431, 437, 439, etc. in electrical and computer engineering and the broader area of data science.
Duncan Hall 2028, 713-348-5132, firstname.lastname@example.org
Office hours: By appointment
Location: Duncan Hall Room 1042
Time: Tuesdays/Thursdays 1:00 to 2:15pm
Duncan Hall 2120, email@example.com
Office hours: TBA
Weekly Q/A Help Session
Meeting Time: TBD
- Course Syllabus
- Course email: elec301TA@gmail.com Use this email to contact the course staff with questions, comments, etc.
- Piazza Course Management Site. It is mandatory that you use this site. All official announcements will be made through Piazza.
- Additional Resources
- Lecture Slides (first half of course)
- Demos and Applets
- MATLAB Tutorial Videos from The MathWorks
- "Signal Processing: A view of the future" Part 1, Part 2 (accessible from Rice campus network)
- Introductory materials on machine learning
- Machine Learning Resources
Wikipedia Machine Learning Portal - https://en.wikipedia.org/wiki/Portal:Machine_learning
- Computing resources
Matlab machine learning toolbox - http://www.mathworks.com/solutions/machine-learning/
Python machine learning - http://scikit-learn.org