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College of Engineering

CS 513 – Applied Machine Learning (4)

Explores machine learning basics (variance and bias, underfitting and overfitting, etc). Reviews linear algebra and Numpy. Examines k-nearest neighbors, linear classification (perceptron and online learning), and linear and non-linear regression. Explores applications in housing price prediction (Kaggle contest) and text classification (sentiment analysis). This course may be subject to Enforced Prerequisites that restrict registration into the course. Check the offerings below for more information.

For more information, contact OSU Ecampus at 800-667-1465 (option 1) or ecampus.ess@oregonstate.edu.

Continue to Registration.

TermCRNSecCrP/NInstructorTypeStatusCapAvailWL CapWL Avail
Sp25553494004Bakos, Y.Online Waitlisted28055
Registration Restrictions
Major Restrictions: +6150, +6160 (Statistics, Data Analytics)
Class Notes: This course requires online proctored testing, which may include testing fees and the use of security measures, such as a scan of your testing environment. Please carefully review online proctor test information at: https://ecampus.oregonstate.edu/services/proctoring/.

Textbooks  [ Textbooks]

Syllabus: Available in Canvas to students enrolled in this course. Computer Science syllabi may also be found on the College of Engineering Course and Syllabus List.
Find textbooks for CS 513 at the OSU Beaver Store (current term only). For questions related to course materials, contact the OSU Beaver Store.

Legend
= Signifies the course as a Baccalaureate Core Course.
= Signifies that fees may apply to the course.
+ = Include restriction.
- = Exclude restriction.
* = Prereq may be taken prior to or simultaneously with this course.