This tutorial is a hands-on complement to the "Tensorflow, deep learning and Recurrent Neural Networks" talk (video, slides). If you are looking for the "Shakespeare" model featured in the talk, you can find it here: tensorflow-rnn-shakespeare.
Install Python 3, then pip(3)-install jupyter, matplotlib and tensorflow.
On Windows, Anaconda is recommended.
The tutorial is in the /tutorial folder
Instructions are in *_playground.ipynb files.
Solutions are in *_solution.ipynb files.
Notebooks execute locally. You can also run on Google Cloud ML Engine using the run-on-cloud-ml-engine.ipynb bash script.
Part 1: tutorial/00_RNN_predictions_playground.ipynb
Part 2: tutorial/01_RNN_generator_playground.ipynb
Part 3: tutorial/02_RNN_generator_temperatures_playground.ipynb
Disclaimer: This is not an official Google product but sample code provided for an educational purpose
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.