We use LSTM, BiLSTM, BERT and SVM with TF-IDF, Word2vec and Bag-of-words to classify this documents to positive (labeled as 1), neutral (labeled as 0) and negative (labeled as 2)
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Updated
Sep 26, 2023 - Jupyter Notebook
We use LSTM, BiLSTM, BERT and SVM with TF-IDF, Word2vec and Bag-of-words to classify this documents to positive (labeled as 1), neutral (labeled as 0) and negative (labeled as 2)
Hierarchical Multi Label Hate Speech and Abusive Language Classification
ML classifier application with Tensorflow and Django/Celery
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