Time Series Neural Networks
TSNN is a deep learning library for time series forecasting built on Keras/Tensorflow. It implements various RNN-based models from recent research papers.
Getting Started
The following instructions will get you a copy of the project up and running on your local machine.
Prerequisites
Conda will set up a virtual environment with the exact version of Python used for development along with all the dependencies needed to run TSNN.
conda create -n tsnn python=3.6
source activate tsnn
Installing
Once you have activated your conda environment, you can easily install the package and all its dependencies from PyPI.
pip install tsnn
The next section provides a quick start guide to using TSNN. A more comprehensive tutorial is detailed in the PackageTesting.ipynb notebook.
Using TSNN
Built With
- Keras - High level Deep Learning library running on top of Tensorflow / Theano / CNTK
- Tensorflow - Library for numerical computation, chosen as Keras backend in TSNN.
Authors
- Sofiene Alouini - Engineering graduate - Machine Learning Enthusiast
