Metadata-Version: 2.0
Name: tsnn
Version: 0.1.3
Summary: Time Series Neural Networks (Keras wrapper)
Home-page: https://github.com/sofienealouini/tsnn
Author: Sofiene Alouini
Author-email: sofiene.alouini@gmail.com
License: UNKNOWN
Description-Content-Type: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: Free for non-commercial use
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: numpy (>=1.13.0)
Requires-Dist: matplotlib (>=2.1.0)
Requires-Dist: pandas (>=0.20.0)
Requires-Dist: scikit-learn (>=0.19.0)
Requires-Dist: tensorflow (>=1.3.0)
Requires-Dist: keras (>=2.0.8)

# Time Series Neural Networks

[![Build Status](https://travis-ci.org/sofienealouini/tsnn.svg?branch=master)](https://travis-ci.org/sofienealouini/tsnn) [![Coverage Status](https://coveralls.io/repos/github/sofienealouini/tsnn/badge.svg?branch=master&service=github)](https://coveralls.io/github/sofienealouini/tsnn?branch=master)



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
```

A comprehensive tutorial on how to use TSNN is provided PackageTesting.ipynb notebook.


## Built With

* [Keras](http://www.dropwizard.io/1.0.2/docs/) - High level Deep Learning library running on top of Tensorflow / Theano / CNTK
* [Tensorflow](https://maven.apache.org/) - Library for numerical computation, chosen as  Keras backend in TSNN.


## Authors

* **Sofiene Alouini** - *Engineering graduate - Machine Learning Enthusiast*




