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Institution:
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Utah Tech University
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Subject:
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Computer Science
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Description:
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For students pursuing degrees in Computer Science or related fields, with an interest in the theory and practice of machine learning. Covers an introduction to supervised and unsupervised learning, including decision trees, neural networks, naive Bayes classifiers and support vector machines. Students will be required to implement machine learning systems. **COURSE LEARNING OUTCOMES (CLOs) At the successful conclusion of this course, students will be able to: 1. Use supervised and unsupervised learning techniques. 2. Implement software learning systems. 3. Evaluate quality of learned systems. 4. Implement software utilizing the results of learning systems. Course fee required. Prerequisites: CS 2420 (Grade C or higher); AND CS 2810 (Grade C or higher); AND CS 3005 (Grade C or higher). SP
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Credits:
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3.00
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Credit Hours:
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Prerequisites:
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Corequisites:
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Exclusions:
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Level:
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Instructional Type:
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Lecture
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Notes:
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Additional Information:
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Historical Version(s):
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Institution Website:
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Phone Number:
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(435) 652-7500
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Regional Accreditation:
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Northwest Commission on Colleges and Universities
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Calendar System:
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Semester
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