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https://github.com/hallowshaw/text-emotion-classification-using-lstm-and-tokenization
This repository provides a machine learning and deep learning pipeline for text emotion detection. It includes a pretrained LSTM model, tokenizer, and preprocessing steps to classify emotions such as joy, sadness, and anger from text input. Easily deployable with provided resources and scripts.
https://github.com/hallowshaw/text-emotion-classification-using-lstm-and-tokenization
emotion-classification emotion-detection feature-engineering lstm nltk nltk-python scikit-learn scikitlearn-machine-learning sentiment-analysis sequential-models text-classification text-classification-multi-label tokenization tokenizer
Last synced: 5 days ago
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This repository provides a machine learning and deep learning pipeline for text emotion detection. It includes a pretrained LSTM model, tokenizer, and preprocessing steps to classify emotions such as joy, sadness, and anger from text input. Easily deployable with provided resources and scripts.
- Host: GitHub
- URL: https://github.com/hallowshaw/text-emotion-classification-using-lstm-and-tokenization
- Owner: hallowshaw
- Created: 2024-12-28T20:56:59.000Z (5 days ago)
- Default Branch: main
- Last Pushed: 2024-12-28T21:02:54.000Z (5 days ago)
- Last Synced: 2024-12-28T22:17:41.660Z (5 days ago)
- Topics: emotion-classification, emotion-detection, feature-engineering, lstm, nltk, nltk-python, scikit-learn, scikitlearn-machine-learning, sentiment-analysis, sequential-models, text-classification, text-classification-multi-label, tokenization, tokenizer
- Language: Jupyter Notebook
- Homepage:
- Size: 17.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0