Name: SWE546_Final_Project
Owner: Bogazici-SWE546-Spring2016
Description: Final Project for data mining
Created: 2016-05-06 02:26:41.0
Updated: 2016-05-06 02:26:41.0
Pushed: 2016-06-04 17:34:18.0
Homepage:
null
Size: 2
Language: null
GitHub Committers
| User | Most Recent Commit | # Commits |
|---|
Other Committers
| User | Email | Most Recent Commit | # Commits |
|---|
README
SWE546_Final_Project
Final Project for data mining
As the final project, you will develop a method for recommendation.
Steps:
- Form groups of two or three. If you prefer to do so, you can also work alone.
- Analyze the public data set given in http://files.grouplens.org/datasets/movielens/ml-10m-README.html
The goal is to develop a recommendation system, by predicting the ratings for unobserved user-movie pairs.
You need to submit a report, preferably as an jupyter notebook, that contains
- the description of the dataset along with snapshots of visualizations
- a mathematical description of the models that you have developed and any features that you have developed. There must be at least two different methods.
- the code for your simulations, should be runnable
- a description and discussion of the evaluation criteria,
- an evaluation of your system along with a comparion of the results by the methods you have proposed
- Submit your report with all the material by 3rd June, 19:00 by a pull request
Optional but recommended:
- Present your results at our final meeting in 3rd June, Friday. 19:00
You can also choose another data set, such as data from a kaggle competition such as
https://www.kaggle.com/c/expedia-hotel-recommendations
