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Lets make a movie recommendation system: Crash Course AI #16

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 Computer Science   |   Science   |   Technology
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Follow along: https://colab.research.google.com/drive/1-v9cw18wTDjaCUlECKHsQnHeisLKyG8U
We need to save Jabril and John Green Bots movie nights. Jabril generally likes action movies and John Green Bot likes romantic movies, but they need to find something that they can both watch and enjoy together. Today, were going to build a movie recommender systems to find that perfect movie. With the help of the LensKit library, our AI will use existing movie ratings from the MovieLens dataset and personalized ratings from Jabril and John Green Bot to perform user-user collaborative filtering. Well then create a Jabril Green Bot hybrid that will average these ratings to try and find something that they both want to watch.

Lenskit documentation: https://java.lenskit.org/documentation/

Our GitHub for this lab: https://github.com/crash-course-ai/lab4-recommender-systems

Crash Course is produced in association with PBS Digital Studios: https://www.youtube.com/pbsdigitalstudios


Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse

Thanks to the following patrons for their generous monthly contributions that help keep Crash Course free for everyone forever:

Eric Prestemon, Sam Buck, Mark Brouwer, Indika Siriwardena, Avi Yashchin, Timothy J Kwist, Brian Thomas Gossett, Haixiang N/A Liu, Jonathan Zbikowski, Siobhan Sabino, Zach Van Stanley, Jennifer Killen, Nathan Catchings, Brandon Westmoreland, dorsey, Kenneth F Penttinen, Trevin Beattie, Erika & Alexa Saur, Justin Zingsheim, Jessica Wode, Tom Trval, Jason Saslow, Nathan Taylor, Khaled El Shalakany, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Tim Curwick, David Noe, Shawn Arnold, William McGraw, Andrei Krishkevich, Rachel Bright, Jirat, Ian Dundore
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#CrashCourse #MachineLearning #ArtificialIntelligence

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