ML-project4-Movie-Recommender-System

A machine learning project for building a movie recommender system using collaborative filtering.

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🎬 Project Overview

This repository demonstrates the construction of a movie recommender system using collaborative filtering techniques. The system suggests movies to users based on their previous ratings and similarities to other users.

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📂 Contents

File/Folder	Description
Project 8 - Movie Recommender System.ipynb	Jupyter Notebook with code & explanations
Project 8 - Recommender Systems.pptx	Project presentation slides
Movie_Id_Titles	Movie titles and IDs mapping
My_Ratings.csv	User ratings dataset
u.data	Movie ratings data
LICENSE	License information for this repository
README.md	This file

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⚙️ Flowchart

Below is a simple flowchart illustrating the movie recommendation process:

flowchart TD
    A[Start] --> B[Load Datasets 📥]
    B --> C[Preprocess Data 🧹]
    C --> D[Build Rating Matrix 🔢]
    D --> E[Apply Collaborative Filtering 🤝]
    E --> F[Generate Recommendations 💡]
    F --> G[Evaluate Model 📊]
    G --> H[End]

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💻 Getting Started

1. Clone the repository:

   git clone https://github.com/mdzaheerjk/ML-project4-Movie-Recommender-System.git

2. Open the Jupyter Notebook:

   • Ensure you have Python and Jupyter installed.
   • Open Project 8 - Movie Recommender System.ipynb to view and run the code.

3. Run the cells:

   • Follow the instructions in the notebook to load the data, preprocess it, build the recommender, and generate movie recommendations.

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🧰 Requirements

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Install dependencies with:

pip install pandas numpy scikit-learn notebook

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🏆 Results

• The system makes personalized movie recommendations based on user ratings.
• You can experiment with different similarity metrics and filtering methods to improve recommendation quality.

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📄 License

This project is licensed under the MIT License.

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👤 Author

mdzaheerjk

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Feel free to fork this repository and enhance the recommender system or adapt it for other recommendation tasks!