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Predict genre of movie from title and description using a Bidirectional LSTM.

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Movie Classifier

Predict the genre of a movie given the title and description.

Please use the included dockerfile to generate a docker image. Inside the project directory, run:

docker build -t movie_classifier . 
docker run -it movie_classifier

It'll take some time to download the packages and create a docker image. Once, that's done you can start classifying movies.

Inside the container, you can run the application using:

python movie_classifier.py --title <movie-title> --description <desc>

In order to run unit tests, run:

python tests.py

You can also retrain the model by running the train.py file. Please check out the help section of the file for more details. You can access it by using:

python train.py --help

Details

  • The dataset is derived from The Movies Dataset on kaggle.
  • The application uses a pytorch implementation of the BiLSTM model for prediction, since LSTM have been shown to perform well in sentence classification tasks.
  • GloVE 6b, 50 dimensional vectors are used in the embedding layer.
  • The dataset (movies_metadata.csv) has been processed to convert the problem from multi-label to a multi-class problem.

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Predict genre of movie from title and description using a Bidirectional LSTM.

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