ngoquanghuy99/Sentiment-classification-of-Amazon-fine-food-reviews
A deep learning model (Bidirectional LSTM) using pretrained word embeddings to do sentiment analysis on Amazon fine food reviews dataset.
Leverages GloVe 100-dimensional word embeddings with bidirectional LSTM architecture to capture contextual sentiment patterns, achieving 93% accuracy on binary classification (positive/negative reviews). Implements end-to-end training and inference pipelines using TensorFlow/Keras, with hyperparameter tuning via `config.py` and command-line prediction interface for real-time review classification.
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Language
Python
License
MIT
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Last pushed
Dec 05, 2020
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