course_outline
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course_outline [2014/08/12 16:55] – nick | course_outline [2014/09/08 17:46] (current) – nick | ||
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====== Course Outline ====== | ====== Course Outline ====== | ||
+ | **wiki: https:// | ||
====== Course Description, | ====== Course Description, | ||
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* Part VI: Student Presentations | * Part VI: Student Presentations | ||
- | **Grading**\\ | ||
- | The course will be graded on the basis of one minor and substantial assignment (10% and 25%), one major in-class presentation and one minor (15 min) project report (15%), and one project (50%). \\ | ||
- | \\ | ||
- | Grades should follow the distribution A (90-100); B (80-89); C (70-79); D (60-60); uh oh (below 60) | ||
**Class Materials** | **Class Materials** | ||
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**References** | **References** | ||
- | | + | Recommended Textbook |
* Jiawei Han, Micheline Kamber and Jian Pei, Data Mining -- Concepts and Techniques. Morgan Kaufmann, Third Edition, 2011. | * Jiawei Han, Micheline Kamber and Jian Pei, Data Mining -- Concepts and Techniques. Morgan Kaufmann, Third Edition, 2011. | ||
- | | + | Reference Books |
* Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Addison Wesley, 2006.\\ | * Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Addison Wesley, 2006.\\ | ||
* Ian H. Witten and Eibe Frank, Data Mining -- Practical Machine Learning Tools and Techniques (2nd Ed.), Morgan Kaufmann, 2005.\\ | * Ian H. Witten and Eibe Frank, Data Mining -- Practical Machine Learning Tools and Techniques (2nd Ed.), Morgan Kaufmann, 2005.\\ |
course_outline.1407862545.txt.gz · Last modified: 2014/08/12 16:55 by nick