在TensorFlow中实现文本分类的卷积神经网络
Github提供了完整的代码：
https://github.com/dennybritz/cnn-text-classification-tf
在这篇文章中，我们将实现一个类似于Kim Yoon的卷积神经网络语句分类的模型。 本文提出的模型在一系列文本分类任务（如情绪分析）中实现了良好的分类性能，并已成为新的文本分类架构的标准基准。
我假设你已经熟悉了应用于NLP的卷积神经网络的基础知识。 如果没有，我建议先阅读NLP的理解卷积神经网络，以获得必要的背景。
Implementing a CNN for Text Classification in TensorFlow
The full code is available on Github.
In this post we will implement a model similar to Kim Yoon’s Convolutional Neural Networks for Sentence Classification. The model presented in the paper achieves good classification performance across a range of text classification tasks (like Sentiment Analysis) and has since become a standard baseline for new text classification architectures.
I’m assuming that you are already familiar with the basics of Convolutional Neural Networks applied to NLP. If not, I recommend to first read over Understanding Convolutional Neural Networks for NLP to get the necessary background.
原文链接：http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
更多教程：http://www.tensorflownews.com/
