uwloo

SYDE 372Introduction to Pattern Recognition

Faculty
Engineering
Last listed
Spring 2020

No longer offered. It was in Waterloo’s course catalog since at least Winter 2020 (as far back as Open Data goes) to Spring 2020 and last ran in Winter 2020. It isn’t in the 2024–25 or later calendars.

When it ran

  1. W20

Ran in 1 term, Winter 2020 to Winter 2020.

Pattern recognition as a process of data analysis. Pattern features as components in a random vector representation. Classification techniques; distance measures in feature space, probabilistic (Bayesian) decision theory, linear discriminants. Clustering and feature extraction. Applications; optical character recognition, speech recognition, industrial robot vision, medical diagnosis, remote sensing and satellite image analysis, fault detection and diagnosis in complex systems such as nuclear reactors. [Offered: W]

Requirements, as last listed

Prereq: (Level at least 3A Biomedical Engineering) or (Level at least 3B Systems Design Engineering) or (Level at least 4A Mechatronics Engineering) or Mechatronics Option or Biomechanics Option

Reviewed on UW Flow

100% liked it43% easy100% useful

From 19 ratings and 6 comments on UW Flow. The most helpful comments, quoted as written, without names. Read them all on UW Flow.

  • Great course - a lot of matrix math but everything is algorithmic. Really interesting assignments.

    Aug 2019 · liked itOn UW FlowRemove this

  • Test questions in-line with lecture slides.
    Be prepared to do a lot of matrix arithmetic if you take this course.
    Assignments were the most useful part of this course

    Aug 2019 · liked itOn UW FlowRemove this

  • Very useful and interesting course for anyone interested in AI and computer vision.

    Apr 2018 · liked itOn UW FlowRemove this

  • A lot of practical knowledge in classifying data. Material is straightforward, though quite a bit more could have been fit into the course.

    Apr 2016 · liked itOn UW FlowRemove this

  • Very straightforward course. Interesting labs and practical content.

    Mar 2015 · liked itOn UW FlowRemove this

Discussed on r/uwaterloo

13 posts and comments in 9 threads mention SYDE 372, December 2012 to December 2024. Quoted word for word, newest first; each reply sits under the post and the comment that started its branch. Search r/uwaterloo for newer posts.

Winter 2022

Suggestions introductory Machine Learning courses? 1 point, 15 comments

“Hi everyone, another post asking for some advice. (And will probably post another post soon about NE or something) Anyhow, I am an upcoming exchange student scouring courses to take in the 2022 Fall …”

u/Mysterious_Glass_798: “… I'll give one example of such a course that may interest you: SYDE372/572 is a course on pattern recognition, which has a gazillion applications in image recognition, natural language processing, medical imaging, etc. …”

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Fall 2021

Fall 2020

Winter 2019

ECE 417 vs SYDE 372 3 points, 3 comments

u/2tripleO: “Trying to decide between ECE 417 and SYDE 372 as a TE next semester. Not sure of my interests yet, but interested in both courses. Does one course provide more practical skills than the other?”

u/dennybang4292: “I haven't taken ECE 417 (will take next term), but SYDE 372 was very enjoyable. Although it wasn't easy, the prof (Alex Wong) is truly passionate about the course and I feel like I learned a lot in the end. …”

u/2tripleO: “I was looking at the course content for SYDE 372 and it seemed to cover a lot of things. Was there enough time to be able cover all that content and learn it well?”

u/dennybang4292: “… &x200B; First, SYDE 372, def worth it if you are interested in Machine Learning but wants to learn fundamental concepts. Though it does not dig too deep into ML, Alex does an amazing job at getting you introduced into how pattern rec works. …”

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systems vs softeng 3 points, 3 comments

“currently unsure of what to do. i feel like i'll have a better chance getting into systems but I like programming and designing stuff. Are you able to take software electives in systems? …”

u/jassmall: “… For technical electives (which only occur in the last 3 terms), there are several software related electives offered within the department (such as SYDE 322, 372, 522, and 575) and you can count courses from other department (like ECE, SE, CS) towards your electives IF you are …”

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SYDE Technical Electives 9 points, 5 comments

u/Aggressive_Sky: “Any SYDE grads take SYDE 372, 522, 552 or 556? How was the overall course content, were the courses useful and or difficult?”

u/Sam_E: “just a heads up, SYDE 522 is at full capacity for winter 2019 term, people in 4B syde can't even enroll now. SYDE 372 was a common one for those interested in ML but heard it was very mechanical (lots of matrix computation)”

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Winter 2016

Any good substitutes to vision courses CS484/473? 3 points, 3 comments

“These two are not offered anymore since all relevant professors have switched their research focus. Any good substitutes?”

u/retsoptidder: “ece 413 - digital signal & image processing syde 372 - introduction to pattern recognition syde 575 - image processing amath 391 - from fourier to wavelets cs 486 - introduction to artificial intelligence stat 441 - statistical learning - classification stat 442 - data …”

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Fall 2012

Check it elsewhere

In the scanned calendars

How it read in each calendar from 1971–72 to 1994–95, newest first. The text is OCR of the scanned pages; years whose wording matches are shown once, from the clearest scan. Each year links to its page on uwloo and to that page of the scanned PDF.

1982–83 to 1994–95 13 calendars

Pattern recognition as a process of data analysis. Pattern features as components in a random vector representation. Classification techniques: distance measures in feature space, probabilistic (Bayesian) decision theory, linear discriminants. Clustering and feature extraction. Applications: optical character recognition, speech recognition, industrial robot vision, medical diagnosis, remote sensing and satellite image analysis, fault detection and diagnosis in complex systems such as nuclear reactors.

Offered Winter · 3 class, 1 tutorial hours a week · 0.5 credit

1978–79 to 1981–82 4 calendars

Pattern Recognition as an information processing problem; recognition and classification of patterns in data; distinguishing features. Probability and Statistics, linear algebra, and calculus are combined with concepts from communication theory and information science to develop techniques of data analysis. Examples include: optical character recognition, automated cytology, disease diagnosis, earthquake prediction, meteorology, aerial photograph analysis, personal credit rating, economic forecasting.

Offered Winter · 3 class, 1 tutorial hours a week · 0.5 credit

Not in the 1972–73 to 1977–78 calendars.

1971–72 1 calendar

Another title: Communications 2, probably a different course under the same number (or a misread scan).

A continuation of 371 with special emphasis on the theories of persuasion and coercion. The design of complex systems which imply a need for individual and social change will be studied.