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TV Script Generation

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.

Project Steps

The project consists of the following steps:

  1. Get and Explore the Data

  2. Implement Preprocessing Functions:

    • Lookup Table
    • Tokenize Punctuation
    • Pre-process all the data and save it
    • Input Batching
  3. Build the Neural Network:

    • Model Architecture
    • Defining Forward and Backpropagation
  4. Neural Network Training

    • Hyperparameters
    • Training
  5. Generate TV Script

Instructions

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.

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Generate your own Seinfeld TV scripts using Recurrent Neural Networks (RNNs)

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