Movie Genre Classification using TensorFlow

This script demonstrates how to train a movie genre classification model using TensorFlow. The model classifies movies into three genres: Western, History, and Musical. Uses the sample_mflix movies collection in Atlas!

Installation

1. Install Python (version 3.6 or above) if you haven't already.

2. Install TensorFlow using pip:

pip3 install tensorflow

3. Install the required additional modules:

pip3 install pymongo

Usage

1. Make sure you have a MongoDB Atlas account set up. If not, sign up for free at https://www.mongodb.com/cloud/atlas.

2. Clone this repository to your local machine or download the files.

3. Open the movies.py script in a text editor.

4. Replace <your_connection_string> with your actual MongoDB Atlas connection string in the client = pymongo.MongoClient('<your_connection_string>') line.

5. Open a terminal or command prompt and navigate to the project directory.

6. Run the script using the following command:

python3 movies.py

This will start the training process and display the progress and accuracy.

7. Once the model is trained, it will be saved as movie_genre_model.keras in the current directory.

Contributing

If you'd like to contribute to this project, feel free to fork the repository and submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

For more information, you can refer to the following documentation:

• TensorFlow Documentation
• Keras Documentation