{"id":28907674,"url":"https://github.com/2000pawan/content_based_movie_recommendation_system","last_synced_at":"2026-05-05T09:31:58.697Z","repository":{"id":299311047,"uuid":"1002623661","full_name":"2000pawan/Content_Based_Movie_Recommendation_System","owner":"2000pawan","description":"A Content-Based Movie Recommendation System built using Streamlit, scikit-learn, and OMDb API, which recommends movies based on their descriptions. 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Posters are fetched live using the OMDb API.\n\nWeb-link:- https://movie-recommender-system-pawan.streamlit.app/\n\n---\n\n## 🚀 Features\n\n- 🔍 Search and select a movie\n- 🎯 Content-based recommendations using TF-IDF + Nearest Neighbors\n- 🖼 Automatically fetch movie posters and plots via OMDb API\n- 🧠 Uses cosine similarity on TF-IDF vectors\n- 📦 Clean and responsive UI built with Streamlit\n- 🛡 Graceful handling of missing posters using placeholders\n\n---\n\n## 📊 Demo Screenshot\n\n![App Screenshot](img.jpg)\n\n---\n\n## 🧠 How It Works\n\n- The dataset contains movies and their descriptions.\n- The `TfidfVectorizer` converts descriptions into numerical vectors.\n- The `NearestNeighbors` model finds the most similar descriptions to the selected movie.\n- For each recommended title, the OMDb API provides a poster and plot.\n- If the poster is not found, a placeholder is shown.\n\n---\n\n## 🛠 Tech Stack\n\n- [Python](https://www.python.org/)\n- [Pandas](https://pandas.pydata.org/)\n- [scikit-learn](https://scikit-learn.org/)\n- [Streamlit](https://streamlit.io/)\n- [OMDb API](https://www.omdbapi.com/)\n\n---\n\n## 📁 Project Structure\n\n    ├── app.py # Main Streamlit app\n    ├── img.jpg # Banner image for the UI\n    ├── movies_content.csv # Movie dataset with titles and descriptions\n    ├── requirements.txt # Python dependencies\n      └── README.md # Project documentation\n---\n\n## 🔧 Installation\n\n1. **Clone the repository**:\n\n       git clone https://github.com/2000pawan/Content_Based_Movie_Recommendation_System.git\n       cd Content_Based_Movie_Recommendation_System\n2. Install dependencies:\n\n       pip install -r requirements.txt\n       Run the app:\n       streamlit run app.py\n---\n\n## 🔑 OMDb API Key\nYou must have a valid OMDb API key.\n\nReplace the default key in app.py:\n\napi_key = \"your_omdb_api_key_here\"\n\n## 📌 Sample Dataset Format\n\ntitle\tdescription\n\nInception\tA thief who steals corporate secrets...\n\nThe Dark Knight\tBatman raises the stakes in his war...\n\nMake sure your CSV has a title and description column.\n\n### 📬 Contact\n\nPawan Yadav\n\nyaduvanshi2000pawan@gmail.com\n\n### 📄 License\n\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F2000pawan%2Fcontent_based_movie_recommendation_system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2F2000pawan%2Fcontent_based_movie_recommendation_system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F2000pawan%2Fcontent_based_movie_recommendation_system/lists"}