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Assignments
COURSEWORK:
Coursework consist of 3 homework assignments and 1 take-home course project on data mining (grading in parentheses):
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IMPORTANT DATES:
| Assignment |
Note
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Out |
Due |
Weight |
| Homework 1 |
similarity measures, similarity search
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Nov 1
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Nov 14
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20%
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| Homework 2 |
SVD, clustering, outliers
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Nov 14 |
Nov 28
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20%
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| Homework 3 |
graphs, text, streams, time series
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Nov 28 |
Dec 11
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20%
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| Final exam |
You are allowed to bring a single, A4-size 'cheat' sheet with your notes
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Dec 11 8:30-10:30AM
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30%
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| Class participation |
Pop-quizzes (any time during class)
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10%
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HOMEWORK:
The goal of the homework is to enable the students to practice the concepts learned in class using real-world datasets.
- ASSIGNMENTS ARE DUE AT THE BEGINNING OF LECTURE ON THE DUE DATE.
- All assignments are to be done individually. Please see the collaboration policy.
- To submit:
- Submit your soft-copy in .pdf as well as all code in .zip on Canvas.
- Return a printed hard-copy on due date in class.
- Make sure your answers are clear and writing is legible (if handwriting).
- See course policies for assignment questions, late submissions, graded homework pick-up.
EXAM
There will be a final exam. It will be closed everything -- no books, slides, computers, etc. You will only be allowed to bring along with you 1 A4-size paper of your own notes ('cheat sheet'), you can use both sides. The final date will be announced during the semester.
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