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contentbasedfiltering

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End-to-End-Movie-Recommendation-System-with-deployment-using-docker-and-kubernetes

Chandru-21 / End-to-End-Movie-Recommendation-System-with-deployment-using-docker-and-kubernetes

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Content Based Recommendation system uses attributes of the content to recommend similar content. It doesn't have a cold-start problem because it works through attributes or tags of the content, such as actors, genres or directors, so that new movies can be recommended right away.

python nlp docker kubernetes machine-learning recommendation-system recommender-system movie-recommendation endtoend streamlit streamlit-webapp endtoendpipeline contentbasedfiltering movierecommendationsystem
  • Updated May 2, 2022
  • Python

gmayuri1904 / Movie-Recommendation-System

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The application uses content based filtering to make recommendations. For every movie selected, 12 recommendations are made based on their cosine similarity with the selected movie. An API feteches the poster image of the movie and displays them in an image grid to the user The database offers nearly 5000 movies to select from

python nlp recommendation-system cosine-similarity contentbasedfiltering
  • Updated Dec 11, 2022
  • Python

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