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Basic concepts and techniques for data mining and machine learning.
Textbook InformationNo required textbook.
Book and Resources For Reference
Homeworks, Quizs, and Projects (tentative)
The grade will be based on written written assignments (HW),
classroom quizs, (QZ), midterm exam (ME), projects (PR), and final exam (FE), as
Exams are closed books and closed notes.
Academic Honesty and Ethical behavior are required in this course, as it is in all courses at Purdue University. The class will be conducted according to the policy written by Professor Gene Spafford. Please take the time to read it carefully. This will be followed unless the instructor provides written documentation of exceptions.
It is allowed and in fact encouraged for students to discuss homework questions. However, you should not look at another student's written/typed answers, and you should not show your written/typed answers to another student. Offences will have consequences ranging from receiving a 0 on the HW to being reported to the school, depending on the seriousness of the offence.
Students are encouraged to talk with the instructor about any questions you have about what is permitted on any particular assignment.