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Next on Netflix

Contributors: Sania Sinha, Keara Hayes, Jarrett Fein, Jana Ratzloff, Dan Smieszny, Kyle Brown

CMSE 202 project: 26th April, 2022

Project Motivation

Can't start a meal without a show to watch? Spent more time deciding on a movie to watch than the actual movie duration? We got you covered! Next on Netflix is a recommendation system, showcasing different approaches.

Watch Next

This module recommends a movie for you to watch based on your last watched movie.

Based on: Term Frequency Inverse Document Frequency
Relevant File: watch_next.ipynb (Courtesy of Keara)

Based on: Ratings and KNN algorithm to compute similarity with cosine distance metric
Relevant File: jana-netflix-project.ipynb (Courtesy of Jana)

Netflix Home

This module contains different ways of creating a Netflix homepage for you- recommending multiple movies taking into consideration your entire watch history.

Based on: Cosine Similarity Matrix
Relevant Files: sanya-netflix-home.ipynb and Draft 1.ipynb (older version) (Courtesy of Sania)

Based on: Keyword matching and weighted scores of number of episodes watched and days since watching
Relevant File: jarrett_prediction_algorithm.ipynb (Courtesy of Jarrett)

Based on: Title similarity in each genre using difflib
Relevant File: dan-homepage.ipynb (Courtesy of Dan)

Other Resources

  • Data Cleaning and get functions for number of episodes, days since watching: data_cleaning_function.ipynb and old_data_cleaning.ipynb (older version)
  • Watch history data: JarrettNetflixViewingHistory.csv, NetflixViewingHistoryDan.csv and NetflixViewingHistoryHome.csv (from Dan, Jarrett & Kyle)
  • Netflix Movie Database: movies.csv and netflix_titles.csv

To use: Just replace Netflix watch history files with yours!
To download your watch history on Netflix: Hover over profile icon > Account > Choose relevant account > View Activity > Scroll to the bottom > Download All (Now, you should have your watch history downloaded as a csv!)

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