Character-level-cnn-tensorflow and Char-CNN-for-Text-Classification

Both tools are competitor TensorFlow implementations of Character-level Convolutional Networks for text classification, meaning users would likely choose one over the other based on factors like implementation details, active development, or specific use-case suitability.

Maintenance 0/25
Adoption 7/25
Maturity 16/25
Community 17/25
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 8/25
Stars: 28
Forks: 11
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 8
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About Character-level-cnn-tensorflow

vietnh1009/Character-level-cnn-tensorflow

Character-level CNN for text classification

This tool helps categorize text documents like news articles or product reviews into predefined groups, even when dealing with very short or informal text. You provide your raw text data, and it classifies each piece, telling you what category it belongs to. This is useful for data analysts, content managers, or anyone needing to sort large volumes of text efficiently.

text categorization content management sentiment analysis prep review classification news topic detection

About Char-CNN-for-Text-Classification

MingtaoGuo/Char-CNN-for-Text-Classification

Character-level Convolutional Networks for Text Classification

This tool helps categorize articles, posts, or any short text snippets into predefined categories like 'sports' or 'business'. You provide a collection of text documents, each with a category label, and the system learns to sort new, unlabeled texts. This is ideal for content managers, researchers, or anyone needing to automatically organize large volumes of textual information.

content-categorization news-classification document-sorting text-analysis information-organization

Scores updated daily from GitHub, PyPI, and npm data. How scores work