dennybritz/cnn-text-classification-tf
A Tensorflow implementation of a convolutional neural network for text classification based on Kim's 2014 paper.
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This repository provides a simplified implementation of a CNN for sentence classification in Tensorflow. The model uses convolutional layers with different filter sizes to capture n-gram features from text, applies dropout for regularization, and performs classification. It includes training and evaluation scripts with configurable hyperparameters like embedding dimension, number of filters, and dropout rate.
Frequently asked
- What is dennybritz/cnn-text-classification-tf?
- A Tensorflow implementation of a convolutional neural network for text classification based on Kim's 2014 paper.
- Is cnn-text-classification-tf open source?
- Yes — dennybritz/cnn-text-classification-tf is open source, released under the Apache-2.0 license.
- What language is cnn-text-classification-tf written in?
- dennybritz/cnn-text-classification-tf is primarily written in Python.
- How popular is cnn-text-classification-tf?
- dennybritz/cnn-text-classification-tf has 5.7k stars on GitHub.
- Where can I find cnn-text-classification-tf?
- dennybritz/cnn-text-classification-tf is on GitHub at https://github.com/dennybritz/cnn-text-classification-tf.