Comparative Analysis of LSTM and RNN for Sentiment Classification of Amazon Reviews

The article presents a practical comparison of RNN and LSTM models for sentiment analysis, a common task in NLP. While valuable for beginners, it lacks depth in exploring advanced techniques like attention mechanisms or pre-trained embeddings. The analysis could benefit from a more rigorous evaluation, including statistical significance testing and comparison against benchmark models.

• •The article implements a binary classification task to classify Amazon reviews as positive or negative.
• •RNN and LSTM models are used for sentiment classification.
• •The article compares the accuracy of each model.