July 2018
Beginner to intermediate
146 pages
3h 39m
English
Content preview from Hands-On Recommendation Systems with Python
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Plot description-based recommender
Our plot description-based recommender will take in a movie title as an argument and output a list of movies that are most similar based on their plots. These are the steps we are going to perform in building this model:
- Obtain the data required to build the model
- Create TF-IDF vectors for the plot description (or overview) of every movie
- Compute the pairwise cosine similarity score of every movie
- Write the recommender function that takes in a movie title as an argument and outputs movies most similar to it based on the plot
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