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https://github.com/gaizkiaadeline/text-classification-using-lstm-and-skip-gram-vectorization
Text classification project using an LSTM model and text vectorization with the Skip-gram technique. The model is designed to classify text data into different labels with flexible hyperparameter tuning options.
https://github.com/gaizkiaadeline/text-classification-using-lstm-and-skip-gram-vectorization
lstm skipgram text-classification
Last synced: 2 days ago
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Text classification project using an LSTM model and text vectorization with the Skip-gram technique. The model is designed to classify text data into different labels with flexible hyperparameter tuning options.
- Host: GitHub
- URL: https://github.com/gaizkiaadeline/text-classification-using-lstm-and-skip-gram-vectorization
- Owner: gaizkiaadeline
- Created: 2024-10-22T04:54:11.000Z (17 days ago)
- Default Branch: main
- Last Pushed: 2024-10-22T05:54:22.000Z (17 days ago)
- Last Synced: 2024-10-23T07:11:32.277Z (16 days ago)
- Topics: lstm, skipgram, text-classification
- Language: Jupyter Notebook
- Homepage:
- Size: 1.75 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Text Classification Using LSTM and Skip-gram Vectorization
Text classification project using an LSTM (Long Short-Term Memory) model and text vectorization with the Skip-gram technique. The task is to classify text data into 20 labels, and the project allows for hyperparameter tuning and modifications to the LSTM architecture.
