intro - CSE572DataMining HuanLiu,CSE,CIDSE,ASU

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04/08/10 CSE 572: Data Mining by Huan  Liu 1 CSE 572 Data Mining Huan Liu, CSE,CIDSE, ASU http://www.public.asu.edu/~huanliu/DM10S/cse572.html
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04/08/10 CSE 572: Data Mining by Huan  Liu 2 CSE 572 Contents of basic and advanced topics Classification, Clustering, Association, and  Applications Format –  An interactive and hands-on course  with ample  opportunities to work, create  and share Paper reading, discussion, project, presentation, or  any learning activities you can suggest Assessment in various ways Class participation, assignments, quizzes, a course  project, presentations, 1 or 2 exams
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04/08/10 CSE 572: Data Mining by Huan  Liu 3 You: our future data mining star, a potential  zillionaire  TAs: Ali Abbasi,  mabbasi2@asu.edu  (key  contact point) Reza,  reza@asu.edu , (project related)      Geoff,  gbarbier@asu.edu , ( paper presentation ) Me: Huan Liu, huanliu@asu.edu Where: Brickyard 566 When: see on the course website, or by appointment “No pain, no gain”, or “As you sow, so you shall  reap”. We will also learn the principle of “No  Free Lunch”.   MyASU will be used,  make sure won’t miss important  announcement and your email address stays current (I push some  information to you via emails sometimes)
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04/08/10 CSE 572: Data Mining by Huan  Liu 4 Course Format What is the effective teaching of graduate data  mining ? Your feedback is keenly sought.  Current research papers – related to your  current research/thesis projects. You can choose one of the textbooks listed. It is  an entry point for you to access related  subjects. The truth is  It is a fast changing field.   Everyone is expected to read research papers  and participate in class discussion. Paper presentations. Project presentations, if time permits.  Presentations will also be evaluated in class. 
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04/08/10 CSE 572: Data Mining by Huan  Liu 5 Point distribution (tentative) Projects (20-25%) Reading/presentation assignment (5%) Exam(s) (40-50%) Assignments (15-20%), and  class participation, quizzes (up to 10%  extra   credit) Late penalty, YES, increasing  exponentially  wrt  the number of days.  Academic integrity   (http://www.public.asu.edu/~huanliu/conduct.html)
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04/08/10 CSE 572: Data Mining by Huan  Liu 6 Research paper reading We welcome your suggestions/recommendations. All  are expected to search for and read the selected papers – part of  the learning process. What is it about (e.g., key idea, basic algorithm)?
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intro - CSE572DataMining HuanLiu,CSE,CIDSE,ASU

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