A movie recommender system using nlp-based techniques called Word Embedding. It will calculate the distance between the most similar movies based on Cosine similarity. You can use other distance measurement techniques like Euclidean Distance or Manhattan Distance. You can also try out Document Embedding instead of Word Embedding.
You can follow my tutorial on youtube ->
No need to install try it out. -> https://moviesrecommendersystemcontent.herokuapp.com/
- pandas
- requests
- streamlit
Must have to satisfy all the requirements
streamlit run app.pyTMDB 5000 Movie Dataset link -> https://www.kaggle.com/datasets/tmdb/tmdb-movie-metadata
Yes, link -> https://developers.themoviedb.org/3/
