CS 441

Fall 2021 All Classes

All Classes

Applied Machine Learning

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Credit: 3 OR 4 hours.

Techniques of machine learning to various signal problems: regression, including linear regression, multiple regression, regression forest and nearest neighbors regression; classification with various methods, including logistic regression, support vector machines, nearest neighbors, simple boosting and decision forests; clustering with various methods, including basic agglomerative clustering and k-means; resampling methods, including cross-validation and the bootstrap; model selection methods, including AIC, stepwise selection and the lasso; hidden Markov models; model estimation in the presence of missing variables; and neural networks, including deep networks. The course will focus on tool-oriented and problem-oriented exposition. Application areas include computer vision, natural language, interpreting accelerometer data, and understanding audio data.

3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225 and CS 361.

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CS 441 class schedule data for fall 2021
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
74468	Online Lecture	AM1	ARRANGED	n.a.	n.a.	Morales Aguirre, M Robles Granda, P	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Info: This course will be taught on the Coursera platform, and will not open to those outside of CS majors. The course will include in-class meetings as scheduled for additional discussion time. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MCS:Computer Sci Online -UIUC, MCS:Computer Sci Online -UIUC, or NDEG:Computer Science Onl-UIUC. Not intended for First Time Freshman students.
74467	Online Lecture	AML	ARRANGED	n.a.	n.a.	Morales Aguirre, M Robles Granda, P	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 3 hours Section Info: This course will be taught on the Coursera platform. The course will include in-class meetings as scheduled for additional discussion time. This section will have one or more proctored online exams. Proctoring options may include fee-based ProctorU and approved testing facilities that carry no fees. For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister Restriction(s): Restricted to Undergrad - Urbana-Champaign.
74471	Online	AMO	ARRANGED	n.a.	n.a.	Morales Aguirre, M Robles Granda, P	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Info: This course is only for students that are in the Computer Science MCS-DS Program. Additional ProctorU fees may apply. Description: The course is intended to support students who wish to apply machine learning methods, and will focus on tool-oriented and problem-oriented exposition. Application areas include computer vision, natural language, interpreting accelerometer data, and understanding audio data. Restriction(s): Restricted to MCS:Computer Sci Online -UIUC or MCS:Computer Sci Online -UIUC.