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Merge pull request #1 from aymericdamien/dev
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‎LICENSE‎

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

‎README.md‎

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# TensorFlow Examples
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Basic code examples for some machine learning algorithms, using TensorFlow library.
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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.
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## Tutorial index
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#### 1 - Introduction
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- Hello World ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/helloworld.py))
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- Basic Operations ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/basic_operations.py))
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- 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))
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- 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))
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#### 2 - Basic Classifiers
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- Nearest Neighbor ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/nearest_neighbor.py))
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- Linear Regression ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/linear_regression.py))
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- Logistic Regression ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/logistic_regression.py))
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- 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))
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- 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))
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- 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))
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#### 3 - Neural Networks
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- Multilayer Perceptron ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/multilayer_perceptron.py))
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- Convolutional Neural Network ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/convolutional_network.py))
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- AlexNet ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/alexnet.py))
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- Reccurent Network ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/recurrent_network.py))
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- 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))
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- 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))
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- 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))
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- Reccurent Network ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3%20-%20Neural%20Networks/recurrent_network.py))
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### 4 - Multi GPU
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- Basic Operations on multi-GPU ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/multigpu_basics.py))
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- 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))
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## Dependencies
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```
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matplotlib
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cuda (to run examples on GPU)
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```
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For more details about TensorFlow installation, you can check [Setup_TensorFlow.md](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/Setup_TensorFlow.md)
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## Dataset
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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).
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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/))
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_Other tutorials are coming soon..._

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