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2014-02-13-Project.html
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2014-02-13-Project.html
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<!DOCTYPE html>
<html>
<head>
<title>Data Mining</title>
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---
# Final Project
---
## Deliverables
+ Project Proposal (due April 9)
+ Code (due April 30)
+ Data (URL or sampled, due April 30)
+ Presentation (May 8)
+ Written Report (due May 14)
---
## Groups
+ 1-3 people
---
## Proposal
+ Informal, not graded
+ A plan for your project
+ After the proposal you should just be executing, not brainstorming
+ Discussions before proposal encouraged
---
## Report
+ Introduction
+ problem, insights, solutions
+ Problem
+ motivation, data set
+ Solution
+ techniques, failures, examples
+ Details
+ parameter tuning, software engineering challenges
+ Related work
+ including resources you used
+ Further work
+ any remaining ideas you have
???
## Notes
+ Length
+ around 2 pages, but more important to hit these points
+ Introduction
+ "gosh, if these insights are true, it would be really
exciting"
+ Problem
+ include problems with your data set
+ Solution
+ if you do clustering, give examples of a cluster you found and
individual data points that it contains
+ Details
+ what commands did you use for particular libraries. Can someone
duplicate your work?
+ Formats
+ PDF, Google Doc
---
## Research Paper
+ [How to write a good research paper](http://research.microsoft.com/en-us/um/people/simonpj/papers/giving-a-talk/writing-a-paper-slides.pdf)
+ But much shorter!
???
## Skip sections
+ No abstract
+ Think paragraphs instead of pages
---
## Presentation
+ ~10 minutes
+ Think: 1 slide per paragraph
+ Focus on images, stories, examples
+ Motivate people to read your paper, don't read it to them
---
## Code
+ Another GitHub repository
+ Public is best, but if private then add Shreyas and me
+ Include README with info on how to run algorithms
+ Suggestion: include your paper
???
## Reproducible
+ Imagine if someone wanted to reproduce your results
+ Also great for portfolio (with Paper)
---
## Data
+ If large, just point to URL in paper and README
+ git is not very good at handling large data files, don't commit large
datasets
+ If very large, talk with me about hosting on Amazon Web Services
+ We'll have computing resources available from Amazon
</textarea>
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