MDGE612
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Foundations of Machine Learning
Graduate Science Education (O)
MD - Cumming School of Medicine
Subject
MDGE - Medical Graduate Education
Description
Basic statistical/computational theories and current libraries for machine learning will be introduced. Content may evolve according to the progress of the field but includes: 1. History and current status of machine learning. 2. Linear models and regularization. 3. Support vector machine and kernel methods. 4. Neural networks (including deep learning). The module introduces both theories and implementations, with a focus on applying the techniques to biological and medical big-data. The level of difficulties may be adjusted according to the diverse backgrounds of the attendees.
Course Attributes
Fee Rate Group(Domestic) - A, Fee Rate Group(International) -B, GFC Hours (1-0)
Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.
Component
LEC
Units
1
Repeat for Credit
No
Subject code
MDGE
Understanding Course Information
Please refer to Course Terminology and Description to better understand how to interpret course information such as GFC Hours, pre-requisites, course levels, etc.