ECE 5420
Last Updated
- Schedule of Classes - May 19, 2024 7:32PM EDT
- Course Catalog - May 19, 2024 7:07PM EDT
Classes
ECE 5420
Course Description
Course information provided by the Courses of Study 2023-2024.
The course will be devoted to understanding, implementation, and applications of various machine learning primitives. This course is intended to have three modules, and within each we will cover basic theory, and implementations. The modules will be supervised learning, unsupervised learning, and finally topics that are motivated by engineering applications such as speech recognition, and recommendation systems. Supervised learning will include regression, support vector machines, decision trees, random forests, naïve Bayes, boosting and bagging. Unsupervised learning includes clustering, k-means, k-NN, principal components analysis and other dimensionality reduction methods. We will give particular emphasis on engineering applications, e.g., text data, hand-writing, music, image, and time series data, and categorical datasets such those in recommendation systems. The course will have a programming component, which will be administered in the form of assignments, and in-class-kaggle competition
When Offered Spring.
Permission Note Enrollment limited to: graduate students.
Prerequisites/Corequisites Prerequisite: MATH 2940, ECE 3100 or STSCI 3080 or ECE 3250 or equivalents.
Regular Academic Session. Choose one lecture and one discussion. Combined with: ECE 4200
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Credits and Grading Basis
4 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- TR Olin Hall 255
- Jan 22 - May 7, 2024
Instructors
Goldfeld, Z
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Additional Information
Instruction Mode: In Person
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Class Number & Section Details
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Meeting Pattern
- F Phillips Hall 101
- Jan 22 - May 7, 2024
Instructors
Goldfeld, Z
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Additional Information
Instruction Mode: In Person
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