Movie Genre Classification

Overview

This project implements a Movie Genre Classification system using Machine Learning with Python. It recommends movies based on user input, utilizing a combination of features like genres, keywords, taglines, cast, and director.

Project Structure

Movie Recommendation System using Machine Learning with Python.ipynb: Jupyter Notebook containing the main code.
movies.csv: Dataset used for training and testing the model.
README.md: This file, providing an overview of the project.

Dependencies

Ensure you have the following Python libraries installed:

numpy
pandas
scikit-learn
difflib

You can install these dependencies using the following command:

pip install numpy pandas scikit-learn


Data Collection and Pre-Processing
The project involves collecting and pre-processing movie data from the movies.csv file.
Selected features include genres, keywords, taglines, cast, and director.
Cosine Similarity
The project uses Cosine Similarity to recommend movies based on user input.
Getting Started
Clone the repository:

bash
git clone https://github.com/AbishekPonmudi/Movie_genre_classification.git


Open the Jupyter Notebook:

bash

jupyter notebook "Movie Recommendation System using Machine Learning with Python.ipynb"
Execute the code cells in the notebook.

Usage
Run the notebook.
Enter your favorite movie when prompted.
Get movie recommendations based on similarity scores.
Contribution
Feel free to contribute to the project by opening issues or creating pull requests. Any suggestions or improvements are highly appreciated.

Acknowledgments
Original Dataset - Mention the source of the dataset.
License
This project is licensed under the MIT License - see the LICENSE file for details.