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Consilium is a movie recommender system that relies on classic k-Nearest-Neighbor collaborative filtering to learn user behavior and compute prediction

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Consilium

Consilium is a single page application that implements a movie recommender system by running machine learning algorithm(s) to make predictions on movie ratings.

[Consilium Live][live] [live]:https://consilium.herokuapp.com/

Instruction for Collaborators

Besides the standard,

$ bundle install
$ npm intall

Set up Redis in memory store by first installing Redis on your Mac or Linux OS

Mac OS X
$ brew install redis

Linux
$ sudo apt-get install redis-server

Setting up Redis on Rails (localhost)

In config/initializers/redis.rb, you will see how Redis is instantiated. The Redis instance will be stored in a global variable $redis and you may call this variable anywhere in the Rails app. For local host development, make sure to use

$redis = Redis.new(:host => 'localhost', :port => 6379)

and comment out the other line because that one is for deployment to Heroku

Redis instance on Heroku

Redis URL can be found by running

$ heroku config | grep REDIS

Redis instance info can be found by running

$ heroku redis:info

Start running

First you need to start your Redis server by typing in

$ redis-server

Now you can start your Rails server

$ rails s

Don't forget webpack!

Regression

The first step of this project is to use gradient descent to fit linear/quadratic functions to univariate/multivariate data set.

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Consilium is a movie recommender system that relies on classic k-Nearest-Neighbor collaborative filtering to learn user behavior and compute prediction

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