A machine learning based movie recommendation app.
- Movie Cocktail suggests new movies based on the selected combination of movies.
- Not sure which movie to watch? Want to watch something similar to movies you've watched before?
- Search and select movies you've already watch, mix them as you wish and get the closest movies to the cocktail.
- Here is the link of the app: moviecocktail
- Let's say you want to watch something 30% like 'the Matrix (1999)' and 70% like 'Titanic (1997)' then you can search for the movies the Matrix (1999) and Titanic (1997), combine them with the ratios of 30% and 70% and find the top ten closest movies to this combination.
- The combination/mix represents the "cocktail". The movie cocktail app suggests top 10 closest movies to the cocktail.
- Note that, the program will work for a single movie as well, so you don't always have to mix the movies.
- These values are basically L2 distances between vectors. There are three different distance measures specified.
- First distance on the top represents the average distance of the cocktail to any movie.
- The second one represents the distance between the cocktail to the specified movie.
- Extra distance info button shows the average distance of the specified movie to any other movie.
- Movie Cocktail uses movie embeddings obtained by a collaborative filtering model trained on 25m movie ratings.
- By using the embedding vectors of selected movies, a new combined embedding vector is generated. After that, it is all about finding the closest L2 distances to the generated new embedding vector.
- You don't have to mix the movies, you can just select a single movie, and find the closest movies to the specified movie. In this case slider value won't matter as long as it is greater than zero.