Machine Learning in Healthcare
Durham
Health & Human Services :: Health Data Science
Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term III (01/19/2021 - 03/12/2021)
Grade Mode: Letter Grading
Term: Spring 2021 - E-term III (01/19/2021 - 03/12/2021)
Grade Mode: Letter Grading
Class Size:
15
CRN: 57256
CRN: 57256
This course covers the foundations of machine learning in healthcare systems including algorithms related to classification and regression prediction in supervised setting, clustering and dimension reduction in an unsupervised setting. Topics include data preprocessing and classification techniques such as logistic regression, support vector machines, KNN, Na'ive Bayes', ensemble methods such as random forests, boosted trees, XGBoost, dimension reduction techniques such as principal components analysis, t-distributed scholastic neighborhood embedding, ISOMAP, locally linear embedding, UMAP, multidimensional scaling. Prereq: HDS 801, HDS 800, HDS 802.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
1/19/2021 | 3/12/2021 | Hours Arranged | ONLINE |