char-cnn-text-classification-tensorflow and Char-level-CNN-for-Text-Classification-in-Keras

These are competitor implementations of the same text classification technique, with one (A) using TensorFlow and the other (B) using Keras.

char-cnn-text-classification-tensorflow
38
Emerging
Char-level-CNN-for-Text-Classification-in-Keras
30
Emerging
Maintenance 0/25
Adoption 9/25
Maturity 8/25
Community 21/25
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 10/25
Stars: 72
Forks: 38
Downloads: —
Commits (30d): 0
Language: Python
License: —
Stars: 6
Forks: 1
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
No License Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About char-cnn-text-classification-tensorflow

lc222/char-cnn-text-classification-tensorflow

Character-level Convolutional Networks for Text Classification论文仿真实现

This project helps machine learning researchers and practitioners understand and replicate the 'Character-level Convolutional Networks for Text Classification' paper. It provides a working implementation of a character-level convolutional neural network, which takes raw text as input and classifies it into predefined categories. This is valuable for those studying or applying advanced text classification techniques.

Machine-Learning-Research Text-Classification Natural-Language-Processing Deep-Learning Academic-Replication

About Char-level-CNN-for-Text-Classification-in-Keras

blues-lin/Char-level-CNN-for-Text-Classification-in-Keras

Character-level Convolution Neural Network for Text Classification in Keras

Related comparisons

char-cnn-text-classification-tensorflow and Character-level-cnn-tensorflow char-cnn-text-classification-tensorflow and char-CNN-text-classification-tensorflow char-cnn-text-classification-tensorflow and Char-CNN-for-Text-Classification char-cnn-text-classification-tensorflow and CharCNN char-cnn-text-classification-tensorflow and Character-level-cnn-pytorch char-cnn-text-classification-tensorflow and Character-level-cnn-tensorflow

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