COMP 352
Spring 2015
| Section:
01
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| Crosslisting:
COMP 552 |
The content of this course will be Artificial Intelligence and Machine Learning. The course will cover search strategies and planning, and will build up to basic machine learning principles and techniques. Includes some programming. |
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| Credit: 1 |
Gen Ed Area Dept:
NSM MATH |
| Course Format: Lecture | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: MATH228 AND COMP212 |
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Fulfills a Requirement for: (COMP)(MATH)(NS&B) |
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Past Enrollment Probability: 75% - 89% |
| SECTION 01 |
Major Readings: Wesleyan RJ Julia Bookstore
Trevor Hastie, Robert Tibshirani and Jerome Friedman, THE ELEMENTS OF STATISTICAL LEARNING: DATA MINING, INFERENCE AND PREDICTION
Kevin Murphy, MACHINE LEARNING A PROBABILISTIC PERSPECTIVE
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Examinations and Assignments:
1 midterm and 1 final. Homework assignments roughly once every 2 weeks. They will each include one programming question and a few theory questions. |
| Instructor(s): Ramyaa,FNU Times: ..T.R.. 01:10PM-02:30PM; Location: SCIE139; |
| Total Enrollment Limit: 30 | | SR major: 10 | JR major: 10 | | |
| Seats Available: -4 | GRAD: 0 | SR non-major: 4 | JR non-major: 4 | SO: 2 | FR: 0 |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 0 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 0 |
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