In this project, you'll generate your own Seinfeld TV scripts using RNNs. You'll be using part of the Seinfeld dataset of scripts from 9 seasons. The Neural Network you'll build will generate a new ,"fake" TV script, based on patterns it recognizes in this training data.
The project consists of the following steps:
-
Get and Explore the Data
-
Implement Preprocessing Functions:
- Lookup Table
- Tokenize Punctuation
- Pre-process all the data and save it
- Input Batching
-
Build the Neural Network:
- Model Architecture
- Defining Forward and Backpropagation
-
Neural Network Training
- Hyperparameters
- Training
-
Generate TV Script
To complete the project, you need to install the following libraries:
You can find the data here. The helper.py
and problem_unittests.py
are helpful files used to finish the project.