Time series prediction and text generation

Quick start

It is recommended you run this project on a GPU enabled system. If you have access to a GPU, you should follow the Keras instructions for running Keras on GPU.

1. Clone the repository, and navigate to the downloaded folder.

git clone https://github.com/ysharc/text-generation.git
cd text-generation

2. Create (and activate) a new environment with Python 3.6 and the numpy package.

   • Linux or Mac:

   conda create --name text-generation python=3.6 numpy
   source activate text-generation
   

   • Windows:

   conda create --name text-generation python=3.6 numpy scipy
   activate text-generation
   

3. Install/Update TensorFlow (for this project, you may use CPU only).

   • Option 1: To install TensorFlow with GPU support, follow the guide to install the necessary NVIDIA software on your system.

   pip install tensorflow-gpu==1.3.0
   

   • Option 2: To install TensorFlow with CPU support only:

   pip install tensorflow==1.3.0
   

4. Install/Update Keras.

pip install keras -U

5. Switch Keras backend to TensorFlow.

   • Linux or Mac:

   KERAS_BACKEND=tensorflow python -c "from keras import backend"
   

   • Windows:

   set KERAS_BACKEND=tensorflow
   python -c "from keras import backend"
   

6. Install a few required pip packages (including OpenCV).

pip install -r requirements.txt

7. Run the notebook and follow instructions

jupyter notebook RNN_project.ipynb