udacity-project-tv-script-generation

This repository contains material related to Udacity's Deep Learning Nanodegree program. It consists of a bunch of tutorial notebooks for various deep learning topics. In most cases, the notebooks lead you through implementing models such as convolutional networks, recurrent networks, and GANs. There are other topics covered such as weight initialization and batch normalization.

Recurrent Neural Networks

TV Script Generation: Train a recurrent neural network to generate scripts in the style of dialogue from Seinfeld.

Dependencies

Configure and Manage Your Environment with Anaconda

Per the Anaconda docs:

Conda is an open source package management system and environment management system for installing multiple versions of software packages and their dependencies and switching easily between them. It works on Linux, OS X and Windows, and was created for Python programs but can package and distribute any software.

Overview

Using Anaconda consists of the following:

Install miniconda on your computer, by selecting the latest Python version for your operating system. If you already have conda or miniconda installed, you should be able to skip this step and move on to step 2.
Create and activate * a new conda environment.

* Each time you wish to work on any exercises, activate your conda environment!

1. Installation

Download the latest version of miniconda that matches your system.

	Linux	Mac	Windows
64-bit	64-bit (bash installer)	64-bit (bash installer)	64-bit (exe installer)
32-bit	32-bit (bash installer)		32-bit (exe installer)

Install miniconda on your machine. Detailed instructions:

2. Create and Activate the Environment

For Windows users, these following commands need to be executed from the Anaconda prompt as opposed to a Windows terminal window. For Mac, a normal terminal window will work.

Git and version control

These instructions also assume you have git installed for working with Github from a terminal window, but if you do not, you can download that first with the command:

conda install git

If you'd like to learn more about version control and using git from the command line, take a look at our free course: Version Control with Git.

Now, we're ready to create our local environment!

Clone the repository, and navigate to the downloaded folder. This may take a minute or two to clone due to the included image data.

git clone https://github.com/udacity/deep-learning-v2-pytorch.git
cd deep-learning-v2-pytorch

Create (and activate) a new environment, named deep-learning with Python 3.6. If prompted to proceed with the install (Proceed [y]/n) type y.
- Linux or Mac:
```
conda create -n deep-learning python=3.6
source activate deep-learning
```
- Windows:
```
conda create --name deep-learning python=3.6
activate deep-learning
```
At this point your command line should look something like: (deep-learning) <User>:deep-learning-v2-pytorch <user>$. The (deep-learning) indicates that your environment has been activated, and you can proceed with further package installations.

Install PyTorch and torchvision; this should install the latest version of PyTorch.

Linux or Mac:

conda install pytorch torchvision -c pytorch

Windows:

conda install pytorch -c pytorch
pip install torchvision

Install a few required pip packages, which are specified in the requirements text file (including OpenCV).

pip install -r requirements.txt

That's it!

Now most of the deep-learning libraries are available to you. Very occasionally, you will see a repository with an addition requirements file, which exists should you want to use TensorFlow and Keras, for example. In this case, you're encouraged to install another library to your existing environment, or create a new environment for a specific project.

Now, assuming your deep-learning environment is still activated, you can navigate to the main repo and start looking at the notebooks:

cd
cd deep-learning-v2-pytorch
jupyter notebook

To exit the environment when you have completed your work session, simply close the terminal window.

arthurpham/udacity-project-tv-script-generation