On completing this course, students will be sufficiently familiar
with the theory, notation, and vocabulary of
pattern recognition and machine learning to be able to pursue matters
of interest in the
current technical literature. They will also have a grasp of key
engineering issues arising in applications.
There is also available, from the same publisher, a companion Computer Manual in MATLAB for this textbook; if you want to use MATLAB for the programming exercises in this course, I urge you buy this manual also---but this book is not required.
"Desk copies" of these two textbooks may be consulted in
CSE Dept office PL 354 when the office is open (but the copy cannot be
taken away). Other
extra copies are available in Dr. Baird's office (PL 380) when he's
there (but, again, these copies can't be taken away).
Grader (for homeworks only):
To ask him questions about homework problems or grades, contact him by email; if you wish, he will arrange to meet you in person. He is also available to explain ideas in this course.
Exams: There will be one "Midterm" exam (in class), probably on Thursday April 9; and one three-hour Final Exam during end-of-semester exam period: these are all closed-book, written exams.
Students may choose not to take a Final Exam; instead, they may carry out either (a) a software project on a research problem from computer vision, docunment image analysis, digital libraries, or Web security, or (b) a literature review report on a narrow technical topic related to this course.(Exams are never repeated: if under extraordinary circumstances a student cannot take an exam, it will be assigned a grade which is the average of the other two exams' grades. If you anticipate that you must---for excellent reasons---miss any of these exams, please give me as much notice in advance as you can, and I will try to arrange for you to take the exam (or some roughly equivalent version of it) before the scheduled exam date.)
Course Site: CSE-426-CSE-326-SP15 Pattern Recognition.
We will use the University's online CourseSite facility to
distribute lecture slides, homework assignments, experimental data sets, and grades.
As soon as you are enrolled in this course, please browse coursesite.lehigh.edu and try to login: if you cannot, send the instructor email.
have questions, ask the instructor: firstname.lastname@example.org.
Accommodations for Students with Disabilities:
If you have a disability for which you are or may be requesting accommodations, please contact both your instructor and the Office of Academic Support Services, University Center 212 (610-758-4152) as early as possible in the semester. You must have documentation from the Academic Support Services office before accommodations can be granted.
Lehigh University endorses The Principles of Our Equitable Community (http://www4.lehigh.edu/diversity/principles).
We expect each member of this class to acknowledge and practice these
Principles. Respect for each other and for differing viewpoints is a
vital component of the learning environment inside and outside the