Welcome Dave’s Fastai Movie Recommender

Movie Recommender based on Fast.AI Collaborative Filtering Model

This file will become your README and also the index of your documentation.


pip install movie_recommender

How to use

This lib provides a get_movie_recs function to get movie recommendations similar to the movie saved in the full_title variable. It also shows how to use gradio to publish a usable version of the movie_recommender.

Click Here to Try the Model Out with Your Favorite Movie

This links to a place in the documentation where you can use the model

This is what it will look like:


A Simple example using the get_movie_recs function

get_movie_recs(full_title='Rushmore (1998)',learn=learn, df_titles=df_titles)
['Rushmore (1998)',
 'Being John Malkovich (1999)',
 'Royal Tenenbaums, The (2001)',
 'Punch-Drunk Love (2002)',
 'Crimes and Misdemeanors (1989)',
 'Heavenly Creatures (1994)',
 'Blue Ruin (2013)',
 'Fargo (1996)',
 'Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1964)',
 'Rififi (Du rififi chez les hommes) (1955)',
 'Lost in Translation (2003)',
 'Great Dictator, The (1940)',
 'Eternal Sunshine of the Spotless Mind (2004)',
 'Hearts of Darkness: A Filmmakers Apocalypse (1991)',
 'Fireworks (Hana-bi) (1997)',
 'Adaptation (2002)',
 'Bob Roberts (1992)',
 'Cabinet of Dr. Caligari, The (Cabinet des Dr. Caligari., Das) (1920)',
 'Ghost World (2001)',
 'Brazil (1985)',
 'Baraka (1992)',
 'City of Lost Children, The (Cité des enfants perdus, La) (1995)',
 'Three Colors: Blue (Trois couleurs: Bleu) (1993)',
 'Player, The (1992)',
 'There Will Be Blood (2007)',
 'Ran (1985)',
 'Sexy Beast (2000)',
 'Nebraska (2013)',
 'Delicatessen (1991)',
 'Tale of Two Sisters, A (Janghwa, Hongryeon) (2003)']