I have developed a recommender system focused on enhancing the movie-watching experience. This system suggests five movies that closely align with the user's preferences and the characteristics of a given movie.
By leveraging advanced machine learning techniques, the recommender system analyzes various features such as genre, director, actors, and user ratings to identify similarities between movies. The goal is to provide personalized recommendations that align with the viewer's taste and preferences.
Techonolgies used: Machine Learning
Programming Language: Python
Softwares Used:
- Jupyter Notebook
- PyCharm IDE
Libraries Used:
- streamlit
- numpy
- pickle
- requests
- pandas
- ast
- nltk
API Used: tmbd api
Dataset Link: https://www.kaggle.com/datasets/tmdb/tmdb-movie-metadata