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Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano Tutorials.
Topics
Dependencies
# TensorFlow-Tutorials
[](https://travis-ci.org/nlintz/TensorFlow-Tutorials)
[](https://www.codacy.com/app/hunkim/TensorFlow-Tutorials)
Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of
Newmu's [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials).
***Topics***
* [Simple Multiplication](00_multiply.py)
* [Linear Regression](01_linear_regression.py)
* [Logistic Regression](02_logistic_regression.py)
* [Feedforward Neural Network (Multilayer Perceptron)](03_net.py)
* [Deep Feedforward Neural Network (Multilayer Perceptron with 2 Hidden Layers O.o)](04_modern_net.py)
* [Convolutional Neural Network](05_convolutional_net.py)
* [Denoising Autoencoder](06_autoencoder.py)
* [Recurrent Neural Network (LSTM)](07_lstm.py)
* [Word2vec](08_word2vec.py)
* [TensorBoard](09_tensorboard.py)
* [Save and restore net](10_save_restore_net.py)
* [Generative Adversarial Network](11_gan.py)
***Dependencies***
* TensorFlow 1.0 alpha
* Numpy
* matplotlib
.
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