Sentiment Analysis on Reviews
An NLP model using LSTMs to classify product reviews as positive or negative.
Overview
This Natural Language Processing (NLP) project focuses on classifying text sentiment. A Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) units was trained on a large dataset of product reviews to determine whether the sentiment of a review is positive or negative.
Challenges & Solutions
Handling nuances of language like sarcasm and context was difficult. The solution involved using pre-trained word embeddings (like GloVe) to provide the model with a richer understanding of word semantics from the start.
Key Features
- Real-time processing and analysis
- Scalable architecture design
- User-friendly interface
- Comprehensive documentation