https://github.com/tgjeon/Keras-Tutorials

Simple tutorials using Keras Framework
https://github.com/tgjeon/Keras-Tutorials

deep-learning feedforward-neural-network keras keras-tutorials tensorflow

Last synced: 3 months ago
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Simple tutorials using Keras Framework

• Host: GitHub
• URL: https://github.com/tgjeon/Keras-Tutorials
• Owner: tgjeon
• Created: 2016-11-04T01:56:27.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2017-03-15T02:14:32.000Z (over 7 years ago)
• Last Synced: 2024-04-13T12:06:19.779Z (7 months ago)
• Topics: deep-learning, feedforward-neural-network, keras, keras-tutorials, tensorflow
• Language: Jupyter Notebook
• Size: 502 KB
• Stars: 267
• Watchers: 15
• Forks: 138
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# Keras-Tutorials

Introduction to deep learning based on Keras framework. These tutorials are direct ports of nlintz's [TensorFlow Tutorials](https://github.com/nlintz/TensorFlow-Tutorials).

*Basic Topics (from nlint'z github)*

* Linear Regression ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/01_linear_regression.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/01_linear_regression.ipynb))

* Logistic Regression ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/02_logistic_regression.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/02_logistic_regression.ipynb))

* Feedforward Neural Network (Multilayer Perceptron) ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/03_net.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/03_net.ipynb))

* Deep Feedforward Neural Network (Multilayer Perceptron with 2 Hidden Layers O.o) ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/04_modern_net.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/04_modern_net.ipynb))

* Convolutional Neural Network ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/05_convolutional_net.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/05_convolutional_net.ipynb))

* Denoising Autoencoder ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/06_autoencoder.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/06_autoencoder.ipynb))

* Recurrent Neural Network (LSTM) ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/07_lstm.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/07_lstm.ipynb))

* Word2vec

* TensorBoard ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/09_tensorboard.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/09_tensorboard.ipynb))

* Save and restore net ([code](https://github.com/tgjeon/Keras-Tutorials/blob/master/10_save_restore_net.py), [notebook](https://github.com/tgjeon/Keras-Tutorials/blob/master/10_save_restore_net.ipynb))

*Advanced Topics*

* Image classification

* Object detection

* Super-Resolution

* Image captioning

* Semantic segmentation

*Note*

* [Deep Learning Glossary](https://github.com/tgjeon/Keras-Tutorials/blob/master/DeepLearningGlossary.md) (for Korean)

: This documentation is translated from blog post on wildml.com (with author's permission)

*Dependencies*

* [Keras v1.2.1](https://github.com/fchollet/keras)

* [TensorFlow v0.12](https://github.com/tensorflow/tensorflow)