This project builds a personalized movie recommendation system that suggests films using content-based filtering with TF-IDF and cosine similarity, along with collaborative filtering for better accuracy. It’s developed with Python and deployed via Streamlit on Render.
Datset is taken from kaggle https://www.kaggle.com/datasets/tmdb/tmdb-movie-metadata
To try out the web demo of Twitter Sentiment Analysis, visit Demo Link. 🚀 https://movie-recommender-system-ui2v.onrender.com
Clone the repository: git clone https://github.com/tanishra/Movie-Recommender-System.git Navigate to the project directory: cd Movie Recommender System Install dependencies: pip install -r requirements.txt Run the application: streamlit app.py 🛠️