PROJECT PROPOSAL: RECOMMENDER SYSTEM
                         

BACKGROUND:

How do we solve this question; Is LUKE CAGE a better movie than SAND CASTLE? Solving this kind question, we would borrow a leave from data scientist on the what is called Recommeder System. According to Wikipedia, A recommender system or a recommendation system (sometimes replacing “system” with a synonym such as platform or engine) is a subclass of information filtering system that seeks to predict the “rating” or “preference” that a user would give to an item.

OBJECTIVE:

The objective of this project is to use recommender system to solve the above question.

METHODOLOGY:

In this project, we would make use of recommender system which can either be done through collaborative or content-based filtering.

The dataset to be used is MovieLense (ml-latest). This can be downloaded from the movielense website (http://grouplens.org/datasets/movielens/latest/).

I tried using R Programming language(environment) to do the analysis, but to no avail, as my OS (Windows 10) would not comply with the Spark Apache software. I then decided to try it out on Databrick Community Edition environment where I would be using both SQL and Python on Spark environment to do the analysis.