MovieRecommendationSystem

This is a content-based Movie Recommendation System built using Python and machine learning libraries. The system suggests movies based on similarity of features such as genre, keywords, tagline, cast, and director.

Features

• Content-based filtering using movie metadata
• Movie similarity calculated using TF-IDF and Cosine Similarity
• Input a movie name and get similar movie recommendations
• Handles missing values in metadata gracefully

Technologies Used

• Programming Language: Python
• Libraries:
  • pandas – data manipulation
  • numpy – numerical operations
  • scikit-learn – TF-IDF Vectorization and Cosine Similarity
  • difflib – finding close matches for user input

Dataset

Source: movies.csv[https://raw.githubusercontent.com/Sourav-10x/MovieRecommendationSystem/refs/heads/main/movies.csv] (from TMDB or similar open-source movie metadata datasets)

• Size: 4803 movies with 24 columns of metadata
• Selected Features for Recommendation:
  • genres
  • keywords
  • tagline
  • cast
  • director

How It Works

1. Data Preprocessing:

   • Load movie dataset
   • Select key metadata features
   • Replace missing values with empty strings
   • Combine all selected features into a single string

2. Feature Vectorization:

   • Use TfidfVectorizer to convert text data into numerical feature vectors

3. Similarity Measurement:

   • Compute cosine similarity between all movies based on their feature vectors

4. Recommendation:

   • Take user input (movie title)
   • Find the closest matching title
   • Recommend top N most similar movies based on cosine similarity

How to Run

This project runs best in Google Colab

Run on Colab

1. Open the notebook:
   Open in Google Colab

2. Upload the movies.csv file when prompted.

3. Run all the cells and enter a movie name when asked.

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Optional: Run Locally

1. Clone the repo:

   git clone https://github.com/Sourav-10x/movie-recommendation-system.git
   cd movie-recommendation-system

2. Install requirements: pip install -r requirements.txt
3. Open the Jupyter Notebook: jupyter notebook

Example Usage

Enter your favourite movie name : Iron Man

Recommended movies:

1. Iron Man 2
2. Avengers: Age of Ultron
3. Captain America: The First Avenger

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