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https://github.com/nlintz/TensorFlow-Tutorials

Simple tutorials using Google's TensorFlow Framework
https://github.com/nlintz/TensorFlow-Tutorials

Last synced: about 2 months ago
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Simple tutorials using Google's TensorFlow Framework

Host: GitHub
URL: https://github.com/nlintz/TensorFlow-Tutorials
Owner: nlintz
Created: 2015-11-10T23:02:28.000Z (about 9 years ago)
Default Branch: master
Last Pushed: 2023-08-20T07:32:57.000Z (over 1 year ago)
Last Synced: 2024-10-15T12:03:30.177Z (about 2 months ago)
Language: Jupyter Notebook
Size: 881 KB
Stars: 6,004
Watchers: 354
Forks: 1,510
Open Issues: 16
Metadata Files:
- Readme: README.md

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README

        # TensorFlow-Tutorials

[![Build Status](https://travis-ci.org/nlintz/TensorFlow-Tutorials.svg?branch=master)](https://travis-ci.org/nlintz/TensorFlow-Tutorials)

[![Codacy Badge](https://api.codacy.com/project/badge/grade/2d3ed69cdbec4249ab5c2f7e4286bb8f)](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