| Course Title: | Introduction to Machine Learning |
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| Class Info.: |
| Class Section: | CS4375.001.13S | Activity Type: | Lecture |
| Class Level: | Undergraduate | Class Number: | 26179 |
| Class Credits: | 3 Credits | Inst. Mode: | Face-to-Face |
| Grading: | Graded - Undergraduate | Session Type: | Regular Academic Session (1) |
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| Status: | Section Status: OPEN Available Seats: 35 Enrolled Total: 25 |
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| Description: | CS 4375 - Introduction to Machine Learning (3 semester hours) Algorithms for creating computer programs that can improve their performance through learning. Topics include: cross-validation, decision trees, neural nets, statistical tests, Bayesian learning, computational learning theory, instance-based learning, reinforcement learning, bagging, boosting, support vector machines, Hidden Markov Models, clustering, and semi-supervised and unsupervised learning techniques. Prerequisites: CS/ SE 3341 and CE/CS/SE/ TE 3345 or equivalent. (3-0) Y |
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| Instructor(s): | |
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| Schedule: | Class Location and Times Location: UT Dallas - Main Campus Friday: 1:00pm-3:45pm ECSS 2.311 Term: Spring 2013 Session Type: Regular Academic Session (1) Starts: January 14, 2013 Ends: May 13, 2013
ECSS Building - Floor 2 - Room 2.311  |
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| Exams: | Date: May 10, 2013 Time: 2:00pm-4:45pm Location: GR 2.530 |
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| College: | Erik Jonsson School of Engineering and Computer Science |
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| Syllabus: | Syllabus for Introduction to Machine Learning (cs4375.001.13s) taught by Haim Schweitzer.
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| Class Evaluation: | A class evaluation for Introduction to Machine Learning (cs4375.001.13s) taught by Haim Schweitzer hasn't been posted. |
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