TSNN is a deep learning library for time series forecasting built on Keras/Tensorflow. It implements various RNN-based models from recent research papers.
The following instructions will get you a copy of the project up and running on your local machine.
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
Once you have activated your conda environment, you can easily install the package and all its dependencies from PyPI.
pip install tsnn
A comprehensive tutorial on how to use TSNN is provided PackageTesting.ipynb notebook.
- Keras - High level Deep Learning library running on top of Tensorflow / Theano / CNTK
- Tensorflow - Library for numerical computation, chosen as Keras backend in TSNN.
- Sofiene Alouini - Engineering graduate - Machine Learning Enthusiast