Capstone Submission #1 for the Harvard University Professional Certificate in Data Science.
This capstone is project 1 out of 2 for the final course in the Harvard University Professional Certificate in Data Science. The goal of the capstone projects are to utlilize skills gained in the program, including data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.
For this project, I created a movie recommendation system using the MovieLens dataset. The version of movielens included in the dslabs package (which was used for some of the exercises in PH125.8x: Data Science: Machine Learning) is just a small subset of a much larger dataset with millions of ratings. I will use the 10M version of the MovieLens dataset to make the computation a little easier.
Inspired by the popular Netflix Kaggle competition that challenged users to create an improved recommendation system (that improved the streaming company's then algorithm's error rate by at least 10%), this assignment aims to accomplish a similar task. The optimal goal is to create a recommendation system algorithm for the provided users that would effectively recommend movies based on the provided features, and to optimize such system with an RMSE score <= 0.87750. I achieved an RMSE of 0.876.