craig-martinson / tv-script-generation-project

Recurrent Neural Networks (RNNs) using TensorFlow

Recurrent Neural Networks (RNNs)

Recurrent Neural Networks (RNNs) project developed for Udacity's Deep Learning Nanodegree. The goal of this project is to generate Simpsons TV scripts using RNNs.

Getting Started

Setup Environment

Clone the Repository

git clone https://github.com/craig-martinson/tv-script-generation-project.git
cd tv-script-generation-project

Setup Linux

Tested on the following environment:

• Ubuntu 16.04.4 LTS
• NVIDIA GTX1080 (driver version 384.130)
• CUDA® Toolkit 9.0
• cuDNN v7.0

Create a Linux Conda environment with CPU backend and upgrade tensorflow:

conda create --name tv-script-project pip python=3.6 numpy jupyter
conda activate tv-script-project
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl
python -m ipykernel install --user --name tv-script-project --display-name "tv-script-project"

Create a Linux Conda environment with GPU backend and upgrade tensorflow:

conda create --name tv-script-project pip python=3.6 numpy jupyter
conda activate tv-script-project
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.8.0-cp36-cp36m-linux_x86_64.whl
python -m ipykernel install --user --name tv-script-project --display-name "tv-script-project"

Setup Windows

Tested on the following environment:

• Windows 10 Pro, 64-bit
• NVIDIA GTX1080 (driver version 385.54)
• CUDA® Toolkit 9.0
• cuDNN v7.0

Create a Windows Conda environment with CPU backend and upgrade tensorflow:

conda create --name tv-script-project pip python=3.6 numpy jupyter tensorflow
conda activate tv-script-project
python -m ipykernel install --user --name tv-script-project --display-name "tv-script-project"

Create a Windows Conda environment with GPU backend and upgrade tensorflow:

conda create --name tv-script-project pip python=3.6 numpy jupyter tensorflow-gpu
conda activate tv-script-project
python -m ipykernel install --user --name tv-script-project --display-name "tv-script-project"

Setup macOS

Tested on the following environment:

• macOS High Sierra

Create a macOS Conda environment with CPU backend and upgrade tensorflow:

conda create --name tv-script-project pip python=3.6 numpy jupyter
conda activate tv-script-project
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.8.0-py3-none-any.whl
python -m ipykernel install --user --name tv-script-project --display-name "tv-script-project"

Jupyter Notebooks

The following jupyter notebooks were developed to support this project:

Description	Link
Project notebook provided by Udacity, demonstrates RNNs with TensorFlow	TV Script Generation Notebook

References

The following resources were used in developing this project:

• Word2Vec Tutorial - The Skip-Gram Model
• TensorFlow Tutorial - Vector Representations of Words