Initial code checkin based on Tensorflow-Examples

Code checkin of code from
https://github.com/aymericdamien/TensorFlow-Examples

Author: mlmurray

LICENSE

@@ -0,0 +1,30 @@
+The MIT License (MIT)
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
+All contributions by Aymeric Damien:
+Copyright (c) 2015, Aymeric Damien.
+All rights reserved.
+
+All other contributions:
+Copyright (c) 2015, the respective contributors.
+All rights reserved.
+
+Each contributor holds copyright over their respective contributions.
+The project versioning (Git) records all such contribution source information.

README.md

@@ -0,0 +1,41 @@
+# TensorFlow Examples
+Code examples for some popular machine learning algorithms, using TensorFlow library. This tutorial is designed to easily dive into TensorFlow, through examples. It includes both notebook and code with explanations.
+
+## Tutorial index
+
+#### 1 - Introduction
+- Hello World ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/1%20-%20Introduction/helloworld.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1%20-%20Introduction/helloworld.py))
+- Basic Operations ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/1%20-%20Introduction/basic_operations.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1%20-%20Introduction/basic_operations.py))
+
+#### 2 - Basic Classifiers
+- Nearest Neighbor ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/2%20-%20Basic%20Classifiers/nearest_neighbor.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2%20-%20Basic%20Classifiers/nearest_neighbor.py))
+- Linear Regression ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/2%20-%20Basic%20Classifiers/linear_regression.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2%20-%20Basic%20Classifiers/linear_regression.py))
+- Logistic Regression ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/2%20-%20Basic%20Classifiers/logistic_regression.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2%20-%20Basic%20Classifiers/logistic_regression.py))
+
+#### 3 - Neural Networks
+- Multilayer Perceptron ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3%20-%20Neural%20Networks/multilayer_perceptron.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3%20-%20Neural%20Networks/multilayer_perceptron.py))
+- Convolutional Neural Network ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3%20-%20Neural%20Networks/convolutional_network.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3%20-%20Neural%20Networks/convolutional_network.py))
+- AlexNet ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3%20-%20Neural%20Networks/alexnet.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3%20-%20Neural%20Networks/alexnet.py))
+- Reccurent Network ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3%20-%20Neural%20Networks/recurrent_network.py))
+
+#### 4 - Multi GPU
+- Basic Operations on multi-GPU ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/4%20-%20Multi%20GPU/multigpu_basics.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4%20-%20Multi%20GPU/multigpu_basics.py))
+
+#### 5 - User Interface (Tensorboard)
+- Graph Visualization ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5%20-%20User%20Interface/graph_visualization.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5%20-%20User%20Interface/graph_visualization.py))
+- Loss Visualization ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5%20-%20User%20Interface/loss_visualization.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5%20-%20User%20Interface/loss_visualization.py))
+
+## Dependencies
+```
+tensorflow
+numpy
+matplotlib
+cuda (to run examples on GPU)
+```
+For more details about TensorFlow installation, you can check [Setup_TensorFlow.md](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/Setup_TensorFlow.md)
+
+## Dataset
+Some examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples (with input_data.py).
+MNIST is a database of handwritten digits, with 60,000 examples for training and 10,000 examples for testing. (Website: [http://yann.lecun.com/exdb/mnist/](http://yann.lecun.com/exdb/mnist/))
+
+_Other tutorials are coming soon...._