2 repositorios
Awesome GitHub RepositoriesConvolutional Text Features
The use of convolutional neural networks to extract hierarchical spatial patterns from text data.
Distinct from Text Feature Extraction: Distinct from Text Feature Extraction: specifically targets the use of CNNs for feature extraction rather than general vectorization.
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Awesome Convolutional Text Features GitHub Repositories
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- nyandwi/machine_learning_complete
Nyandwi/machine_learning_complete
4,983Ver en GitHubThis is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi
Uses convolutional layers to identify hierarchical patterns in text for category prediction.
Jupyter Notebookcomputer-visiondata-analysisdata-science - gaussic/text-classification-cnn-rnn
gaussic/text-classification-cnn-rnn
4,301Ver en GitHubThis project is a TensorFlow-based supervised text categorizer designed for Chinese natural language processing. It utilizes a hybrid neural network architecture that combines convolutional and recurrent layers to map raw Chinese text to predefined categories. The system integrates convolutional neural networks for local feature extraction and recurrent neural networks for analyzing sequential dependencies. It employs character-level tokenization and word embeddings to represent text as numerical tensors. The implementation covers the end-to-end machine learning pipeline, including text prep
Extracts hierarchical spatial patterns and local features from text using CNNs.
Pythonchineseclassificationcnn
