README.md

Dependencies

    sbt >= 1.4.7

Should be available by default on the IC Cluster. Otherwise, refer to each project installation instructions.

Dataset

Download the ml-100k.zip dataset in the data/ folder:

> mkdir data
> cd data
> wget http://files.grouplens.org/datasets/movielens/ml-100k.zip   

Check the integrity of the file with (it should give the same number as below):

> md5 -q ml-100k.zip
0e33842e24a9c977be4e0107933c0723 

Unzip:

> unzip ml-100k.zip

Personal Ratings

Add your ratings in the 'data/personal.csv' file, by providing a numerical rating between [1,5] for at least 20 movies. For example, to rate the 'Toy Story' movie with '5', modify this line:

1,Toy Story (1995),

to this:

1,Toy Story (1995),5

Do include your own ratings in your final submission so we can check your answers against those provided in your report.

Usage

Compute predictions

> sbt 'runMain predict.Predictor'

Compute recommendations

> sbt 'runMain recommend.Recommender'

Package for submission

Update the name, maintainer fields of build.sbt, with the correct Milestone number, your ID, and your email.

Package your application:

> sbt 'show dist'

You should should see an output like:

[info] Your package is ready in [...]/target/universal/m1_your_id-1.0.zip

Combine this package, alongside your report and any other files mentioned in the Milestone description (see Section Deliverables). Submit to the TA for grading.

References

Essential sbt: https://www.scalawilliam.com/essential-sbt/