This is the Linux app named cnn-text-classification-tf whose latest release can be downloaded as cnn-text-classification-tfsourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
cnn-text-classification-tf
DESCRIPTION:
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution filters to extract n-gram features that are then pooled and fed into a classifier. The project includes scripts for training, evaluation, and data handling, making it easy to run experiments on datasets such as movie reviews or other labeled text collections. By breaking down the model into understandable components, it serves as a practical reference for students and practitioners learning how deep learning models handle text beyond traditional bag-of-words approaches.
Features
- TensorFlow implementation of CNN for sentence and text classification
- Data preprocessing and embedding utilities included
- Support for multiple convolution filter sizes
- Training and evaluation scripts ready to run
- Educational and research-oriented reference code
- Apache-2.0 open-source license
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/cnn-text-clasification.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.