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| title: Movie Recommender System | |
| emoji: 🎥 | |
| colorFrom: purple | |
| colorTo: blue | |
| sdk: streamlit | |
| sdk_version: 1.17.0 | |
| app_file: app.py | |
| license: apache-2.0 | |
| ## Movie Recommender System | |
| A movie recommendation system, or a movie recommender system, is an ML-based approach to filter or predict the users’ film preferences using techinques like : | |
| - popularity-based | |
| - content-based | |
| - collabrative filtering | |
| In this, project I have used content-based filtering to fiter movies with similar tags (concatenated strings of story, gernre, and title column) | |
| ## Links : | |
| - #### Hugging Face Space Link : [Click Me](https://huggingface.co/spaces/akshatsanghvi/movie-recommender-system) | |
| - #### Kaggle Dataset (Bollywood) : [Click Me](https://www.kaggle.com/datasets/pncnmnp/the-indian-movie-database) | |
| - #### Kaggle Dataset (Hollywood) : [Click Me](https://www.kaggle.com/datasets/neha1703/movie-genre-from-its-poster?select=MovieGenre.csv) | |
| ## After you click on the HF link you'll see two buttons, | |
| #### "Recommend" Button : Recommends 5 similar movies from the same country as of movie. | |
| #### "🌍" Button : Recommends 10 similar movies from the world. | |
| ## Step 1: | |
|  | |
| ## Step 2: | |
|  | |
| ## Step 3: | |
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