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https://github.com/alexeyev/cnn-for-sentence-classification-in-keras

based on paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim

https://github.com/alexeyev/cnn-for-sentence-classification-in-keras

Science Score: 10.0%

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    CITATION.cff file
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    Links to: arxiv.org
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    Scientific vocabulary similarity
    Low similarity (6.3%) to scientific vocabulary

Keywords

deep-learning keras-implementations natural-language-processing nlp
Last synced: 6 months ago · JSON representation

Repository

based on paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim

Basic Info
  • Host: GitHub
  • Owner: alexeyev
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 701 KB
Statistics
  • Stars: 4
  • Watchers: 4
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Fork of alexander-rakhlin/CNN-for-Sentence-Classification-in-Keras
Topics
deep-learning keras-implementations natural-language-processing nlp
Created over 9 years ago · Last pushed over 9 years ago

https://github.com/alexeyev/CNN-for-Sentence-Classification-in-Keras/blob/master/ 

# Convolutional Neural Networks for Sentence Classification

Training convolutional network for classification tasks. 


Based on "Convolutional Neural Networks for Sentence Classification" by Yoon Kim, [link](http://arxiv.org/pdf/1408.5882v2.pdf). Inspired by Denny Britz article "Implementing a CNN for Text Classification in TensorFlow", [link](http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/). 


Code is a fork of this implementation [link](https://github.com/alexander-rakhlin/CNN-for-Sentence-Classification-in-Keras)

## What's different in this fork

* Python3
* a focus on reusing pretrained word vectors
* a few code-decomposition-related modifications
* using argparse for remote configurable execution
* trying to implement configuration as close to the one in the paper as possible (comments are welcome)
* methods for working with datasets in a standard .csv (text, class_label) format

## TODO

* L2 regularization
* ...

## Dependencies

* [Keras](http://keras.io/) 
* [Tensorflow](https://www.tensorflow.org/)

Code is easily portable to keras/[Theano](http://deeplearning.net/software/theano/install.html#install), 
Tensorflow-specific code is only in the GPU usage configuration part

Owner

  • Name: Anton Alekseev
  • Login: alexeyev
  • Kind: user

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