In this project, I implemented a model to generate Seinfeld TV scripts using RNNs. The dataset was part of the Seinfeld dataset of scripts from 9 seasons. The Neural Network generates new, "fake" TV script, based on patterns it recognizes in this training data.
For best experience with managing dependency I advise you install Anconda or miniconda.
Create a virtual environment with conda
conda create --name deep-learning python=3
Activate environment.
source activate deep-learning
Install dependencies.
pip install -r requirements.txt
Download or clone this seinfeld-tv-script-generation repository. Launch the app with jupyter-notebook.
jupyter-notebook dlnd_tv_script_generation.ipynb
Run all code cells in the notebook (This will take a while to run on a CPU as the code will construct and train a recurrent neural network, preferably you should run on a GPU).
You can already view a sample generated script in generated_script_1.txt.
Generated scripts closely resembles actual scripts from Seinfeld.