├── LICENSE
└── README.md


/LICENSE:
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 1 | The MIT License (MIT)
 2 | 
 3 | Copyright (c) 2016 Alexander Usoltsev
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/README.md:
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 1 | # Tensorflow RNN to Events Prediction
 2 | **[NOTE]**: *This notebook was made with [Tensorflow v.0.8.0](https://github.com/tensorflow/tensorflow/releases/tag/v0.8.0) and code is not compatible with the newest release of Tensorflow. For the moment I don't have time to upgrade the code so you can use notebook more as an illustration of GDELT dataset and time series analysis.*
 3 | 
 4 | Tensorflow Recurrent Neural Network (RNN) model to analyse Time Series in GDELT News dataset to predict future events.
 5 | 
 6 | This Google Datalab notebook shows how to create a simple RNN model to perform analysis of GDELT news events dataset.
 7 | 
 8 | # Installation
 9 | To run this notebook, please follow these steps:
10 | * Create Datalab project in Google Cloud Platform: https://cloud.google.com/datalab/docs/quickstart (do not worry about payment options, default quota is enought to run this demo notebook for free).
11 | * Upload notebook [GDC Meetup Paris GDELT-skflow-RNN](https://github.com/marsbroshok/tensorflow-rnn-events-prediction/blob/master/GDC%20Meetup%20Paris%20GDELT-skflow-RNN.ipynb) to your Datalab envirement.
12 | * Enjoy!
13 | 
14 | 
15 | # Additional info
16 | Please, check [presentation slides](https://docs.google.com/presentation/d/1EoUpLG11NDkKg00ay-YKo_RooQP9LY2RRt2RPFemdF8/edit?usp=sharing) based on this notebook.
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19 | 
20 | _______________
21 | Alexander Usoltsev, Cirruseo (Paris), 2016 (c)
22 | 
23 | 


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