Movie Recommendation App

Overview

The Movie Recommendation App is a machine learning-based web application that suggests movies based on user preferences. This project utilizes content-based filtering to recommend similar movies based on a selected movie title. The app is built using Python, Streamlit, Pandas, and Scikit-learn.

Features

• Recommend similar movies based on a selected title
• User-friendly interface built with Streamlit
• Uses TF-IDF Vectorization and Cosine Similarity for recommendations
• Lightweight and easy to deploy

Tech Stack

• Frontend: Streamlit
• Backend: Python
• Libraries Used: Pandas, NumPy, Scikit-learn, Streamlit, Requests

Installation & Setup

1. Clone the repository:

   git clone https://github.com/vshnvii/movie-recommendation-app.git
   cd movie-recommendation-app

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On macOS/Linux
   venv\Scripts\activate     # On Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Run the application:

   streamlit run app.py

Usage

1. Open the app in your browser.
2. Enter or select a movie title from the list.
3. Click the "Recommend" button to get a list of similar movies.
4. Explore the recommended movies and enjoy!

📸 App Preview

App Screenshot

Dataset

The dataset used in this project is sourced from TMDb and preprocessed for better recommendations. It includes movie titles, genres, descriptions, and other metadata.

Must See

TMDb in india has been banned by Jio, so make sure to use/open the app on any other network except Jio

Future Improvements

• Add collaborative filtering for better recommendations
• Integrate a movie trailer preview feature
• Deploy the app on Heroku or Streamlit Sharing